Logo
  • What’s New in Revision 0.8.0
    • New Features
    • Dependency Updates
    • Breaking Changes

🚀 Getting Started

  • 5-minute quickstart
    • Installing SpectroChemPy
    • Getting Started
    • Working with Spectroscopic Data
      • Loading Data
    • Exploring the Data
      • Understanding the NDDataset object
      • Data Visualization
      • Data Selection and Manipulation
      • Mathematical Operations
      • Other Operations
    • Data Processing Techniques
      • Spectral Smoothing
      • Baseline Correction
    • Advanced Analysis
      • IRIS Processing example
      • Other Advanced Analysis Techniques
    • Next Steps 🎯
  • Installation guide
    • Prerequisites
    • Installing Python
      • Conda Package Managers (Recommended)
      • Installation Steps
      • Alternative Installation Methods
    • Installing SpectroChemPy
      • Create Environment
      • Install Package
    • Additional Resources
      • Installation Guide for Windows
        • Requirements
        • Environment Setup
        • Installing SpectroChemPy
        • Verifying Installation
        • Additional Tips
          • Creating a Permanent Environment Shortcut
        • Next Steps
      • Installation Guide for Mac OSX and Linux
        • Requirements
        • Environment Setup
        • Install SpectroChemPy
        • Verifying Installation
        • Next Steps
      • Install in Google Colaboratory (Colab)
        • Introduction
        • Quick Start
        • Installation
        • Working with Data
          • Directly loading Example Files
          • Using File Explorer
          • Using Google Drive
          • Using Git Repository
      • Optional Dependencies
        • Overview
        • Examples and Testing Data
        • Scientific Computing Extensions
          • Cantera
        • GUI Support
          • Qt Backend
        • Troubleshooting
      • Installation from Sources
        • Prerequisites
          • Git Installation
        • Getting the Source Code
        • Installation Methods
        • Verifying Installation
        • Updating SpectroChemPy
  • Example's gallery
    • Core functionalities
      • How to use NDDataset
      • Import / Export
      • Plotting datasets
      • Project Management
        • How to use NDDataset
          • NDDataset creation and plotting example
          • NDDataset coordinates example
          • Units manipulation examples
          • NDDataset creation and plotting example
        • Import / Export
          • Reading datasets
          • Loading an IR (omnic SPG) experimental file
          • Loading Bruker OPUS files
          • Loading of experimental 1D NMR data
          • Loading RAMAN experimental file
          • Reading Renishaw WiRE files
        • Plotting datasets
          • Using plot_multiple to plot several datasets on the same figure
          • Introduction to the plotting librairie
        • Project Management
          • Project creation
    • Analysis NDDataset
      • Decomposition
      • Cross-decomposition
      • Curvefitting
        • Decomposition
          • EFA example
          • EFA (Keller and Massart original example)
          • FastICA example
          • 2D-IRIS analysis example
          • MCR-ALS example (adapted from Jaumot et al. 2005)
          • MCR-ALS with kinetic constraints
          • NMF analysis example
          • PCA example (iris dataset)
          • PCA analysis example
          • SIMPLISMA example
        • Cross-decomposition
          • PLS regression example
        • Curvefitting
          • Fitting 1D dataset
          • Solve a linear equation using LSTSQ
    • Processing NDDataset
      • Apodization
      • Baseline
      • Denoising
      • filtering
      • Processing NMR datasets
      • Processing Raman datasets
        • Apodization
          • Exponential window multiplication
          • Sine bell and squared Sine bell window multiplication
        • Baseline
          • NDDataset baseline correction
        • Denoising
          • Denoising a 2D Raman spectrum
          • Removing cosmic ray spikes from a Raman spectrum
        • filtering
          • Savitky-Golay and Whittaker-Eilers smoothing of a Raman spectrum
        • Processing NMR datasets
          • Analysis CP NMR spectra
          • Processing NMR spectra (slicing, baseline correction, peak picking, peak fitting)
          • Processing Relaxation measurement
        • Processing Raman datasets
          • Processing RAMAN spectra
  • Getting help
    • GitHub Issues
    • GitHub Discussions
    • Stack Overflow
    • Documentation
    • Contribute

📚 User's Guide & Tutorials

  • Introduction
    • About this user’s guide
    • What to do if questions arise
    • How to get started
      • Writing and executing SpectroChemPy scripts
      • Loading the API
    • Where to go next?
  • Import & Export
    • Import Data in SpectroChemPy
      • Generic read command
      • Using a specific reader
      • Using relative or absolute pathnames
      • Good practices
        • Use relative paths
        • Use os or pathlib packages
          • Another default search directory: datadir
      • Reading directories
      • Additional options for reading directories
      • Reading files from a ZIP archive
    • Import IR Data
      • Supported IR File Formats
      • Detailled Tutorials
        • Import of OMNIC files
          • Import spg file
          • Import of .spa files
          • Handling Metadata
          • Error Handling
          • Advanced Data Operations
        • Import of Bruker OPUS files
          • Basic loading of OPUS file
          • Loading given type of OPUS spectra
          • Reading OPUS file Metadata
          • Acting on a parameter
        • Import/Export of JCAMP-DX files
  • Plotting
    • Load the API
    • Loading the data
    • Preparing the data
    • Selecting the output window
    • Default plotting
    • Changing the aspect of the plot
      • Change the NDDataset.preferences
    • Adding titles and annotations
    • Changing the plot style using matplotlib style sheets
    • Create your own style
    • Changing the type of plot
    • Plotting 1D datasets
    • Plotting several dataset on the same figure
    • Overview of the main configuration parameters
  • Processing
    • Slicing NDDatasets
      • What is the slicing ?
      • Slicing of NDDatasets
        • Slicing with indexes
        • Slicing with coordinates
    • Basic transformations
      • Masking data
      • Transposition
      • Changing units
    • Mathematical operations
      • Ufuncs (Universal Numpy’s functions)
      • List of UFuncs working on NDDataset:
        • Functions affecting magnitudes of the number but keeping units
        • Functions affecting magnitudes of the number but also units
        • Functions that require no units or dimensionless units for inputs. Returns dimensionless objects.
        • Functions that return numpy arrays (Work only for NDDataset)
        • Trigonometric functions. Require unitless data or radian units.
        • Hyperbolic functions
        • Unit conversions
        • Binary Ufuncs
      • Usage
        • Unary functions
          • Functions affecting magnitudes of the number but keeping units
          • Functions affecting magnitudes of the number but also units
          • Functions that require no units or dimensionless units for inputs. Returns dimensionless objects.
          • Functions that return numpy arrays (Work only for NDDataset)
          • Trigonometric functions. Require dimensionless/unitless dataset or radians.
          • Angle units conversion
          • Hyperbolic functions
        • Binary functions
          • Arithmetic
      • Complex or hypercomplex NDDatasets
    • Filtering, Smoothing and Denoising
      • The Filter processor
        • Moving average
        • Convolution with window filters
        • Savitzky-Golay filter
        • Whittaker-Eilers filter
      • Filtering using API or NDDataset methods.
        • The smooth method
          • Window size influence
        • Convolution with windows
        • Savitzky-Golay filter:savgol
        • Whittaker-eilers filter : whittaker
    • Baseline corrections
      • The Baseline processor
        • How it works?
        • Example
        • Overview of the other model
          • Polynomial
        • Multivariate approach
      • Baseline correction using NDDataset or API methods
        • Detrending
          • Constant trend
          • Linear trend
          • Polynomial trend
          • Detrend independently on several data segment
        • basc
        • Rubberband
        • Code snippet for ‘advanced’ baseline correction
    • Denoising
      • Denoising 2D spectra
      • Removing cosmic rays spike from Raman spectra
        • Median filter
        • despike method
    • Apodization
      • Introduction
        • Plot of the Real and Imaginary original data
        • Exponential multiplication
          • Shifted apodization
        • Other apodization functions
          • Gaussian-Lorentzian apodization
          • Shifted Gaussian-Lorentzian apodization
          • Apodization using sine window multiplication
    • Time domain baseline correction (NMR)
    • One-dimensional (1D) Fourier transformation
      • FFT of 1D NMR spectra
      • Preprocessing
        • Line broadening
        • Zero-filling
        • Time domain baseline correction
        • Magnitude calculation
        • Power spectrum
    • Real Fourier transform
    • FTIR interferogram processing
      • Comparison with the OMNIC processing.
    • Alignment of datasets
      • Example
      • Methods for alignments
        • inner method
        • first method
        • last method
      • Alignment along several dimensions
  • Analysis
    • Peak Maxima Finding
      • Loading an experimental dataset
      • Find maxima by manual inspection of the plot
      • Find maxima with an automated method: find_peaks()
        • Default behaviour
        • Options of find_peaks()
        • More on peak properties
          • Prominence
          • Width
        • A code snippet to display properties
    • Peak Integration
    • Fitting
      • Solving a linear equation using the least square method (LSTSQ)
      • Least square with non-negativity constraint (NNLS)
      • NDDataset modelling using non-linear optimisation method
        • Baseline correction
        • Peak finding
        • Fitting script
          • Syntax for parameters definition
    • Principal Component Analysis
      • Introduction
      • Loading of the dataset
      • Running a PCA
    • Partial Least Squares Regression (PLSRegression)
      • Introduction
      • Loading of the dataset
      • Running PLSRegression
    • MCR ALS
      • Introduction
      • The (minimal) dataset
      • Initial guess and MCR ALS optimization
        • Case of initial spectral profiles
          • ALS Optimization
          • More information about the MCRALS estimator
          • Solutions
          • A basic illustration of the rotational ambiguity
        • Guessing the concentration profile with PCA + EFA
          • Use of PCA to assess the number of pure species
          • Determination of initial concentrations using EFA
      • Augmented datasets
  • API Configuration
    • General information
    • Loglevel
      • Error handling
  • Core objects
    • NDDataset
      • The NDDataset object
        • Table of Contents
        • Introduction
        • 1D-Dataset (unidimensional dataset)
          • nD-Dataset (multidimensional dataset)
        • About dates and times
        • About the history attribute
        • Units
        • Coordinates
        • Labels
      • More insight on coordinates
        • Sharing coordinates between dimensions
        • Setting coordinates using set_coordset
          • Syntax 1
          • Syntax 2
        • Adding several coordinates to a single dimension
        • Math operations on coordinates
        • Summary of the coordinate setting syntax
      • Methods to create NDDataset
        • Create a dataset from a function
        • Using numpy-like constructors of NDDatasets
        • Copying existing NDDataset
        • Importing from external datasets
    • Project
      • Project management
        • Project creation
        • Remove an element from a project
        • Get project’s elements
        • Saving and loading projects
          • Saving
          • Loading
    • Script

🔍 Reference

  • Public API reference
    • Loading the API
    • The NDDataset Object
      • spectrochempy.NDDataset
        • NDDataset
          • NDDataset.II
          • NDDataset.IR
          • NDDataset.RI
          • NDDataset.RR
          • NDDataset.T
          • NDDataset.acquisition_date
          • NDDataset.author
          • NDDataset.ax
          • NDDataset.axT
          • NDDataset.axec
          • NDDataset.axecT
          • NDDataset.axex
          • NDDataset.axey
          • NDDataset.comment
          • NDDataset.coordnames
          • NDDataset.coordset
          • NDDataset.coordtitles
          • NDDataset.coordunits
          • NDDataset.created
          • NDDataset.data
          • NDDataset.description
          • NDDataset.dimensionless
          • NDDataset.dims
          • NDDataset.directory
          • NDDataset.divider
          • NDDataset.dtype
          • NDDataset.fig
          • NDDataset.fignum
          • NDDataset.filename
          • NDDataset.filetype
          • NDDataset.has_complex_dims
          • NDDataset.has_data
          • NDDataset.has_defined_name
          • NDDataset.has_units
          • NDDataset.history
          • NDDataset.id
          • NDDataset.imag
          • NDDataset.is_1d
          • NDDataset.is_complex
          • NDDataset.is_empty
          • NDDataset.is_float
          • NDDataset.is_integer
          • NDDataset.is_interleaved
          • NDDataset.is_labeled
          • NDDataset.is_masked
          • NDDataset.is_quaternion
          • NDDataset.labels
          • NDDataset.limits
          • NDDataset.local_timezone
          • NDDataset.m
          • NDDataset.magnitude
          • NDDataset.mask
          • NDDataset.masked_data
          • NDDataset.meta
          • NDDataset.modeldata
          • NDDataset.modified
          • NDDataset.name
          • NDDataset.ndaxes
          • NDDataset.ndim
          • NDDataset.origin
          • NDDataset.parent
          • NDDataset.real
          • NDDataset.roi
          • NDDataset.shape
          • NDDataset.size
          • NDDataset.suffix
          • NDDataset.timezone
          • NDDataset.title
          • NDDataset.umasked_data
          • NDDataset.unitless
          • NDDataset.units
          • NDDataset.value
          • NDDataset.values
          • NDDataset.abs
          • NDDataset.absolute
          • NDDataset.add_coordset
          • NDDataset.all
          • NDDataset.amax
          • NDDataset.amin
          • NDDataset.any
          • NDDataset.arange
          • NDDataset.argmax
          • NDDataset.argmin
          • NDDataset.around
          • NDDataset.asfortranarray
          • NDDataset.astype
          • NDDataset.atleast_2d
          • NDDataset.average
          • NDDataset.clip
          • NDDataset.close_figure
          • NDDataset.component
          • NDDataset.conj
          • NDDataset.conjugate
          • NDDataset.coord
          • NDDataset.coordmax
          • NDDataset.coordmin
          • NDDataset.copy
          • NDDataset.cumsum
          • NDDataset.delete_coordset
          • NDDataset.diag
          • NDDataset.diagonal
          • NDDataset.dump
          • NDDataset.empty
          • NDDataset.empty_like
          • NDDataset.eye
          • NDDataset.fromfunction
          • NDDataset.fromiter
          • NDDataset.full
          • NDDataset.full_like
          • NDDataset.geomspace
          • NDDataset.get_axis
          • NDDataset.get_labels
          • NDDataset.identity
          • NDDataset.is_units_compatible
          • NDDataset.ito
          • NDDataset.ito_base_units
          • NDDataset.ito_reduced_units
          • NDDataset.linspace
          • NDDataset.load
          • NDDataset.loads
          • NDDataset.logspace
          • NDDataset.max
          • NDDataset.mean
          • NDDataset.min
          • NDDataset.ones
          • NDDataset.ones_like
          • NDDataset.pipe
          • NDDataset.plot
          • NDDataset.ptp
          • NDDataset.random
          • NDDataset.remove_masks
          • NDDataset.round
          • NDDataset.round_
          • NDDataset.save
          • NDDataset.save_as
          • NDDataset.set_complex
          • NDDataset.set_coordset
          • NDDataset.set_coordtitles
          • NDDataset.set_coordunits
          • NDDataset.set_hypercomplex
          • NDDataset.set_quaternion
          • NDDataset.sort
          • NDDataset.squeeze
          • NDDataset.std
          • NDDataset.sum
          • NDDataset.swapaxes
          • NDDataset.swapdims
          • NDDataset.take
          • NDDataset.to
          • NDDataset.to_array
          • NDDataset.to_base_units
          • NDDataset.to_reduced_units
          • NDDataset.to_xarray
          • NDDataset.transpose
          • NDDataset.var
          • NDDataset.zeros
          • NDDataset.zeros_like
      • Coordinates-related objects
        • spectrochempy.Coord
          • Coord
        • spectrochempy.CoordSet
          • CoordSet
    • Creating NDDataset
      • Basic creation methods
        • spectrochempy.empty
          • empty
        • spectrochempy.zeros
          • zeros
        • spectrochempy.ones
          • ones
        • spectrochempy.full
          • full
        • spectrochempy.empty_like
          • empty_like
        • spectrochempy.zeros_like
          • zeros_like
        • spectrochempy.ones_like
          • ones_like
        • spectrochempy.full_like
          • full_like
        • spectrochempy.eye
          • eye
        • spectrochempy.identity
          • identity
        • spectrochempy.random
          • random
        • spectrochempy.diag
          • diag
      • Creation from existing data
        • spectrochempy.fromfunction
          • fromfunction
        • spectrochempy.fromiter
          • fromiter
      • Creation from numerical ranges
        • spectrochempy.arange
          • arange
        • spectrochempy.linspace
          • linspace
        • spectrochempy.logspace
          • logspace
        • spectrochempy.geomspace
          • geomspace
      • Select data in a NDDataset
        • spectrochempy.take
          • take
    • Import/export
      • Import a NDataset from external source
        • spectrochempy.load
          • load
        • spectrochempy.read
          • read
          • Examples using spectrochempy.read
        • spectrochempy.read_carroucell
          • read_carroucell
        • spectrochempy.read_csv
          • read_csv
        • spectrochempy.read_ddr
          • read_ddr
        • spectrochempy.read_dir
          • read_dir
        • spectrochempy.read_hdr
          • read_hdr
        • spectrochempy.read_jcamp
          • read_jcamp
        • spectrochempy.read_labspec
          • read_labspec
          • Examples using spectrochempy.read_labspec
        • spectrochempy.read_wire
          • read_wire
          • Examples using spectrochempy.read_wire
        • spectrochempy.read_wdf
          • read_wdf
          • Examples using spectrochempy.read_wdf
        • spectrochempy.read_mat
          • read_mat
        • spectrochempy.read_matlab
          • read_matlab
          • Examples using spectrochempy.read_matlab
        • spectrochempy.read_omnic
          • read_omnic
          • Examples using spectrochempy.read_omnic
        • spectrochempy.read_opus
          • read_opus
          • Examples using spectrochempy.read_opus
        • spectrochempy.read_quadera
          • read_quadera
        • spectrochempy.read_sdr
          • read_sdr
        • spectrochempy.read_soc
          • read_soc
        • spectrochempy.read_spa
          • read_spa
        • spectrochempy.read_spc
          • read_spc
        • spectrochempy.read_spg
          • read_spg
        • spectrochempy.read_srs
          • read_srs
        • spectrochempy.read_topspin
          • read_topspin
          • Examples using spectrochempy.read_topspin
        • spectrochempy.read_zip
          • read_zip
        • spectrochempy.read_carroucell
          • read_carroucell
        • spectrochempy.load_iris
          • load_iris
          • Examples using spectrochempy.load_iris
        • spectrochempy.download_nist_ir
          • download_nist_ir
      • Export a NDDataset
        • spectrochempy.NDDataset.save
        • spectrochempy.NDDataset.save_as
        • spectrochempy.write
          • write
          • Examples using spectrochempy.write
        • spectrochempy.write_csv
          • write_csv
        • spectrochempy.write_excel
          • write_excel
        • spectrochempy.write_jcamp
          • write_jcamp
        • spectrochempy.write_mat
          • write_mat
        • spectrochempy.write_matlab
          • write_matlab
        • spectrochempy.write_xls
          • write_xls
        • spectrochempy.to_array
          • to_array
        • spectrochempy.to_xarray
          • to_xarray
    • Plotting
      • spectrochempy.plot
        • plot
        • Examples using spectrochempy.plot
      • spectrochempy.plot_1D
        • plot_1D
      • spectrochempy.plot_pen
        • plot_pen
      • spectrochempy.plot_scatter
        • plot_scatter
      • spectrochempy.plot_scatter_pen
        • plot_scatter_pen
      • spectrochempy.plot_with_transposed
        • plot_with_transposed
      • spectrochempy.plot_bar
        • plot_bar
      • spectrochempy.plot_2D
        • plot_2D
      • spectrochempy.plot_map
        • plot_map
      • spectrochempy.plot_stack
        • plot_stack
        • Examples using spectrochempy.plot_stack
      • spectrochempy.plot_image
        • plot_image
      • spectrochempy.plot_3D
        • plot_3D
      • spectrochempy.plot_surface
        • plot_surface
      • spectrochempy.plot_waterfall
        • plot_waterfall
      • spectrochempy.plot_multiple
        • plot_multiple
        • Examples using spectrochempy.plot_multiple
      • spectrochempy.multiplot
        • multiplot
      • spectrochempy.multiplot_image
        • multiplot_image
      • spectrochempy.multiplot_lines
        • multiplot_lines
      • spectrochempy.multiplot_map
        • multiplot_map
      • spectrochempy.multiplot_scatter
        • multiplot_scatter
      • spectrochempy.multiplot_stack
        • multiplot_stack
      • spectrochempy.multiplot_with_transposed
        • multiplot_with_transposed
      • spectrochempy.show
        • show
        • Examples using spectrochempy.show
    • Processing
      • Transpose-like operations
        • spectrochempy.transpose
          • transpose
        • spectrochempy.swapdims
          • swapdims
      • Changing number of dimensions
        • spectrochempy.squeeze
          • squeeze
      • Changing type
        • spectrochempy.set_complex
          • set_complex
      • Joining or splitting datasets
        • spectrochempy.concatenate
          • concatenate
          • Examples using spectrochempy.concatenate
        • spectrochempy.stack
          • stack
      • Indexing
        • spectrochempy.diag
          • diag
        • spectrochempy.diagonal
          • diagonal
        • spectrochempy.take
          • take
      • Sorting
        • spectrochempy.sort
          • sort
          • Examples using spectrochempy.sort
      • Minimum and maximum
        • spectrochempy.argmin
          • argmin
        • spectrochempy.argmax
          • argmax
        • spectrochempy.coordmin
          • coordmin
        • spectrochempy.coordmax
          • coordmax
        • spectrochempy.amin
          • amin
        • spectrochempy.amax
          • amax
        • spectrochempy.min
          • min
        • spectrochempy.max
          • max
        • spectrochempy.ptp
          • ptp
      • Clipping and rounding
        • spectrochempy.clip
          • clip
        • spectrochempy.around
          • around
        • spectrochempy.round
          • round
      • Algebra
        • spectrochempy.dot
          • dot
          • Examples using spectrochempy.dot
        • spectrochempy.SVD
          • SVD
        • spectrochempy.LSTSQ
          • LSTSQ
        • spectrochempy.NNLS
          • NNLS
      • Logic functions
        • spectrochempy.all
          • all
        • spectrochempy.any
          • any
      • Sums, integal, difference
        • spectrochempy.sum
          • sum
        • spectrochempy.cumsum
          • cumsum
        • spectrochempy.trapezoid
          • trapezoid
        • spectrochempy.simpson
          • simpson
      • Complex
        • spectrochempy.conj
          • conj
        • spectrochempy.conjugate
          • conjugate
        • spectrochempy.abs
          • abs
        • spectrochempy.absolute
          • absolute
      • Masks
        • spectrochempy.remove_masks
          • remove_masks
      • Units manipulation
        • spectrochempy.Unit
          • Unit
        • spectrochempy.Quantity
          • Quantity
        • spectrochempy.to
          • to
        • spectrochempy.to_base_units
          • to_base_units
        • spectrochempy.to_reduced_units
          • to_reduced_units
        • spectrochempy.ito
          • ito
        • spectrochempy.ito_base_units
          • ito_base_units
        • spectrochempy.ito_reduced_units
          • ito_reduced_units
        • spectrochempy.is_units_compatible
          • is_units_compatible
        • spectrochempy.set_nmr_context
          • set_nmr_context
      • Mathematical operations
        • spectrochempy.mc
          • mc
        • spectrochempy.ps
          • ps
      • Statistical operations
        • spectrochempy.mean
          • mean
        • spectrochempy.average
          • average
        • spectrochempy.std
          • std
        • spectrochempy.sum
          • sum
        • spectrochempy.var
          • var
      • Baseline correction
        • spectrochempy.Baseline
          • Baseline
        • spectrochempy.autosub
          • autosub
        • spectrochempy.get_baseline
          • get_baseline
        • spectrochempy.basc
          • basc
        • spectrochempy.detrend
          • detrend
          • Examples using spectrochempy.detrend
        • spectrochempy.asls
          • asls
        • spectrochempy.snip
          • snip
          • Examples using spectrochempy.snip
      • Fourier transform
        • spectrochempy.fft
          • fft
          • Examples using spectrochempy.fft
        • spectrochempy.ifft
          • ifft
        • spectrochempy.ht
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        • spectrochempy.fsh
          • fsh
        • spectrochempy.fsh2
          • fsh2
      • Phasing
        • spectrochempy.pk
          • pk
          • Examples using spectrochempy.pk
        • spectrochempy.pk_exp
          • pk_exp
      • Time-domain processing
        • Offset correction
          • spectrochempy.dc
        • Zero-filling
          • spectrochempy.zf
          • spectrochempy.zf_auto
          • spectrochempy.zf_double
          • spectrochempy.zf_size
        • Rolling
          • spectrochempy.cs
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          • spectrochempy.roll
          • spectrochempy.rs
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          • spectrochempy.bartlett
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          • spectrochempy.hamming
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          • spectrochempy.hann
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          • spectrochempy.em
          • spectrochempy.gm
          • spectrochempy.sp
          • spectrochempy.sine
          • spectrochempy.qsin
          • spectrochempy.sinm
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          • Filter
        • spectrochempy.savgol
          • savgol
        • spectrochempy.smooth
          • smooth
        • spectrochempy.whittaker
          • whittaker
        • spectrochempy.denoise
          • denoise
          • Examples using spectrochempy.denoise
        • spectrochempy.despike
          • despike
          • Examples using spectrochempy.despike
      • Alignment, interpolation
        • spectrochempy.align
          • align
        • spectrochempy.interpolate
          • interpolate
      • Miscellaneous
        • spectrochempy.pipe
          • pipe
    • Analysis
      • Linear regression
        • spectrochempy.LSTSQ
          • LSTSQ
        • spectrochempy.NNLS
          • NNLS
      • Non-linear optimization and curve fit
        • spectrochempy.Optimize
          • Optimize
      • Partial Least Square regression
        • spectrochempy.PLSRegression
          • PLSRegression
      • Evolving factor analysis
        • spectrochempy.EFA
          • EFA
      • Integral inversion solver for spectroscopic data
        • spectrochempy.IRIS
          • IRIS
        • spectrochempy.IrisKernel
          • IrisKernel
      • Multivariate Curve Resolution - Alternating Least Squares
        • spectrochempy.MCRALS
          • MCRALS
      • Independant Component Analysis
        • spectrochempy.FastICA
          • FastICA
      • Non-Negative Matrix Factorization
        • spectrochempy.NMF
          • NMF
      • Singular value decomposition and Principal component analysis
        • spectrochempy.PCA
          • PCA
        • spectrochempy.SVD
          • SVD
      • SIMPLe to use Interactive Self-modeling Mixture Analysis
        • spectrochempy.SIMPLISMA
          • SIMPLISMA
      • Utilities
        • Lineshape models
          • spectrochempy.gaussianmodel
          • spectrochempy.lorentzianmodel
          • spectrochempy.voigtmodel
          • spectrochempy.asymmetricvoigtmodel
          • spectrochempy.sigmoidmodel
          • spectrochempy.polynomialbaseline
        • Find peaks
          • spectrochempy.find_peaks
        • Kinetic
          • spectrochempy.ActionMassKinetics
          • spectrochempy.PFR
    • Project management
      • spectrochempy.Project
        • Project
          • Project.allitems
          • Project.allnames
          • Project.datasets
          • Project.datasets_names
          • Project.filename
          • Project.filetype
          • Project.id
          • Project.meta
          • Project.name
          • Project.parent
          • Project.projects
          • Project.projects_names
          • Project.scripts
          • Project.scripts_names
          • Project.suffix
          • Project.add_dataset
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          • Project.copy
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          • Project.remove_all_dataset
          • Project.remove_all_project
          • Project.remove_dataset
          • Project.remove_project
          • Project.save
          • Project.save_as
    • Scripting
      • spectrochempy.Script
        • Script
      • spectrochempy.run_script
        • run_script
        • Examples using spectrochempy.run_script
      • spectrochempy.run_all_scripts
        • run_all_scripts
    • Utilities
      • Logging
        • spectrochempy.set_loglevel
          • set_loglevel
          • Examples using spectrochempy.set_loglevel
        • spectrochempy.get_loglevel
          • get_loglevel
        • spectrochempy.debug_
          • debug_
        • spectrochempy.info_
          • info_
          • Examples using spectrochempy.info_
        • spectrochempy.warning_
          • warning_
        • spectrochempy.error_
          • error_
          • Examples using spectrochempy.error_
      • Misc
        • spectrochempy.show_versions
          • show_versions
      • File
        • spectrochempy.pathclean
          • pathclean
  • Glossary
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  • Papers citing SpectroChemPy
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  • See also
SpectroChemPy v0.8.0
  • Adding your examples to the gallery
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Adding your examples to the gallery

If you have any nice examples to add to the SpectroChemPy gallery, they are more than welcome. They will allow other users to see the API in operation.

There are two ways to do this:

  • Use the discussion forums and attach your files, which we will take into account after revisions, mentioning of course the origin and the possible copyright.

  • Create a pull request: For this operation, if you are a newcomer with the git version system, please refer to the Developer’s Guide section .

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© Copyright 2014-2025 - A.Travert & C.Fernandez @ LCS. Last updated on Mar 20, 2025.