Logo
0.6.10
SpectroChemPy version:
  • Home
  • What’s new in revision 0.6.10
    • New features
    • Bug fixes
    • Breaking changes
    • Deprecations
  • Release notes
    • Version 0.6
      • What’s new in revision 0.6.10
        • New features
        • Bug fixes
        • Breaking changes
        • Deprecations
      • What’s new in revision 0.6.9
        • Bug fixes
      • What’s new in revision 0.6.8
        • New features
        • Bug fixes
        • Breaking changes
      • What’s new in revision 0.6.7
        • New features
        • Bug fixes
      • What’s new in revision 0.6.6
        • New features
        • Bug fixes
        • Deprecations
      • What’s new in revision 0.6.5
        • Bug fixes
      • What’s new in revision 0.6.4
        • New features
        • Bug fixes
        • Breaking changes
        • Deprecations
      • What’s new in revision 0.6.3
        • New features
      • What’s new in revision 0.6.2
        • New features
        • Bug fixes
        • Breaking changes
        • Deprecations
      • What’s new in revision 0.6.1
        • Breaking changes
        • Deprecations
    • Version 0.5
      • What’s new in revision 0.5.5
        • New features
        • Bug fixes
      • What’s new in revision 0.5.4
        • Bug fixes
      • What’s new in revision 0.5.3
        • New features
        • Bug fixes
      • What’s new in revision 0.5.2
        • New features
        • Bug fixes
      • What’s new in revision 0.5.1
        • New features
        • Bug fixes
      • What’s new in revision 0.5.0 [2023-01-11]
        • New features
        • Breaking changes
    • Version 0.4
      • What’s new in revision 0.4.10 [2023-01-07]
        • New features
        • Bug fixes
      • What’s new in revision 0.4.9 [2023-01-05]
        • New features
        • Bug fixes
      • What’s new in revision 0.4.7 [2022-05-16]
        • Bug fixes
      • What’s new in revision 0.4.6 [2022-05-16]
        • New features
        • Bug fixes
        • Deprecations
      • What’s new in revision 0.4.5 [2022-04-09]
        • New features
        • Bug fixes
      • What’s new in revision 0.4.4 [2022-03-22]
        • New features
      • What’s new in revision 0.4.3 [2022-03-20]
        • New features
      • What’s new in revision 0.4.2 [2022-03-16]
        • New features
        • Deprecations
        • Bug fixes
      • What’s new in revision 0.4.1 [2022-03-14]
        • Breaking changes
        • New features
        • Bug fixes
    • Version 0.3
      • What’s new in revision 0.3.3 [2022-03-9]
        • New features
        • Bug fixes
      • What’s new in revision 0.3.2 [2022-01-31]
        • New features
        • Bug fixes
      • What’s new in revision 0.3.1 [2022-01-21]
        • New features
      • What’s new in revision 0.3.0 [2022-01-20]
        • New features
        • Bug fixes
    • Version 0.2
      • What’s new in revision 0.2.23 [2022-01-16]
        • Bug fixes
      • What’s new in revision 0.2.22 [2022-01-10]
        • Bug fixes
      • What’s new in revision 0.2.21 [2022-01-09]
        • New features
        • Bug fixes
      • What’s new in revision 0.2.18 [2022-01-05]
        • New features
        • Bug fixes
      • What’s new in revision 0.2.17 [2021-11-29]
        • New features
        • Bug fixes
      • What’s new in revision 0.2.16 [2021-11-11]
        • New features
        • Bug fixes
      • What’s new in revision 0.2.15 [2021-03-29]
        • New features
        • Bug fixes
      • What’s new in revision 0.2.14 [2021-02-25]
        • New features
        • Bug fixes
      • What’s new in revision 0.2.13 [2021-02-23]
        • Bug fixes
      • What’s new in revision 0.2.12 [2021-02-23]
        • Bug fixes
      • What’s new in revision 0.2.11 [2021-02-17]
        • Bug fixes
      • What’s new in revision 0.2.10 [2021-02-14]
        • New features
        • Bug fixes
      • What’s new in revision 0.2.9 [2021-11-29]
        • Bug fixes
      • What’s new in revision 0.2.8
        • New features
        • Bug fixes
      • What’s new in revision 0.2.7
        • New features
        • Bug fixes
      • What’s new in revision 0.2.6
        • New features
        • Bug fixes
      • What’s new in revision 0.2.5
        • New features
        • Bug fixes
      • What’s new in revision 0.2.4
        • New features
        • Bug fixes
      • What’s new in revision 0.2.0
        • New features
        • Bug fixes
    • Version 0.1
      • Revisions 0.1.0 to 0.1.19

Getting Started

  • Why SpectroChemPy ?
    • Designed for Open Science
    • Open Source Software on an Open-Source Platform
    • Powered by Python
    • Why NOT SpectroChemPy ?
  • Overview
    • NDDataset, the main object
      • Display dataset information
      • Plotting a dataset
      • Slicing a dataset
      • Maths on datasets
      • Processing a dataset
        • Smoothing
        • Baseline correction
      • Analysis
        • IRIS processing
  • Examples
  • Installation
    • Prerequisites
    • Installation of SpectroChemPy
      • Installation Guide for Mac OSX
        • Installation using Conda
        • Installation using pip
        • Check the Installation
      • Installation Guide for Windows
        • Installation using Conda
        • Installation using pip
        • Check the Installation
      • Installation from sources (master or develop versions)
        • Installing git
        • Cloning the repository locally
        • Create a conda environment
        • Install SpectroChemPy in this environment
        • Updating SpectroChemPy
      • Install in Google Colaboratory (Colab)
        • Load and install SpectroChemPy with pip
        • Load data files
      • Install optional dependencies
        • Examples and test data
        • Cantera
        • QT

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?
  • Core objects
    • NDDataset
      • The NDDataset object
        • 1D-Dataset (unidimensional dataset)
          • nD-Dataset (multidimensional dataset)
        • About the 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
        • 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 dataset
    • Project
      • Project management
        • Project creation
        • Remove an element from a project
        • Get project’s elements
        • Saving and loading projects
          • Saving
          • Loading
    • Script
  • Import & Export
    • Import Data
      • Dialog boxes
      • Import with explicit directory or file pathnames
        • A good practice: use relative paths
        • Good practice: use os or pathlib modules
      • Another default search directory: datadir
      • File selector widget
    • Import IR Data
      • Supported file formats
      • Import of OMNIC files
        • a) import spg file
          • Acquisition dates and y axis
          • The order of spectra
        • b) Import of .spa files
      • Import of Bruker OPUS files
      • Import/Export of JCAMP-DX files
  • 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
    • 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
    • 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
        • Widget for “advanced” baseline corrections
    • 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
  • 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

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.preferences
          • 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.align
          • NDDataset.all
          • NDDataset.amax
          • NDDataset.amin
          • NDDataset.any
          • NDDataset.arange
          • NDDataset.argmax
          • NDDataset.argmin
          • NDDataset.around
          • NDDataset.asfortranarray
          • NDDataset.asls
          • NDDataset.astype
          • NDDataset.atleast_2d
          • NDDataset.autosub
          • NDDataset.average
          • NDDataset.bartlett
          • NDDataset.basc
          • NDDataset.blackmanharris
          • NDDataset.clip
          • NDDataset.close_figure
          • NDDataset.component
          • NDDataset.concatenate
          • NDDataset.conj
          • NDDataset.conjugate
          • NDDataset.coord
          • NDDataset.coordmax
          • NDDataset.coordmin
          • NDDataset.copy
          • NDDataset.cs
          • NDDataset.cumsum
          • NDDataset.dc
          • NDDataset.delete_coordset
          • NDDataset.denoise
          • NDDataset.despike
          • NDDataset.detrend
          • NDDataset.diag
          • NDDataset.diagonal
          • NDDataset.dot
          • NDDataset.download_nist_ir
          • NDDataset.dump
          • NDDataset.em
          • NDDataset.empty
          • NDDataset.empty_like
          • NDDataset.eye
          • NDDataset.fft
          • NDDataset.find_peaks
          • NDDataset.fromfunction
          • NDDataset.fromiter
          • NDDataset.fsh
          • NDDataset.fsh2
          • NDDataset.full
          • NDDataset.full_like
          • NDDataset.general_hamming
          • NDDataset.geomspace
          • NDDataset.get_axis
          • NDDataset.get_baseline
          • NDDataset.get_labels
          • NDDataset.gm
          • NDDataset.hamming
          • NDDataset.hann
          • NDDataset.ht
          • NDDataset.identity
          • NDDataset.ifft
          • NDDataset.is_units_compatible
          • NDDataset.ito
          • NDDataset.ito_base_units
          • NDDataset.ito_reduced_units
          • NDDataset.linspace
          • NDDataset.load
          • NDDataset.load_iris
          • NDDataset.logspace
          • NDDataset.ls
          • NDDataset.max
          • NDDataset.mc
          • NDDataset.mean
          • NDDataset.min
          • NDDataset.ones
          • NDDataset.ones_like
          • NDDataset.pipe
          • NDDataset.pk
          • NDDataset.pk_exp
          • NDDataset.plot
          • NDDataset.plot_1D
          • NDDataset.plot_2D
          • NDDataset.plot_3D
          • NDDataset.plot_bar
          • NDDataset.plot_image
          • NDDataset.plot_map
          • NDDataset.plot_multiple
          • NDDataset.plot_pen
          • NDDataset.plot_scatter
          • NDDataset.plot_scatter_pen
          • NDDataset.plot_stack
          • NDDataset.plot_surface
          • NDDataset.plot_waterfall
          • NDDataset.ps
          • NDDataset.ptp
          • NDDataset.qsin
          • NDDataset.random
          • NDDataset.read
          • NDDataset.read_carroucell
          • NDDataset.read_csv
          • NDDataset.read_ddr
          • NDDataset.read_dir
          • NDDataset.read_hdr
          • NDDataset.read_jcamp
          • NDDataset.read_labspec
          • NDDataset.read_mat
          • NDDataset.read_matlab
          • NDDataset.read_omnic
          • NDDataset.read_opus
          • NDDataset.read_quadera
          • NDDataset.read_sdr
          • NDDataset.read_soc
          • NDDataset.read_spa
          • NDDataset.read_spc
          • NDDataset.read_spg
          • NDDataset.read_srs
          • NDDataset.read_topspin
          • NDDataset.read_wdf
          • NDDataset.read_wire
          • NDDataset.read_zip
          • NDDataset.remove_masks
          • NDDataset.roll
          • NDDataset.round
          • NDDataset.round_
          • NDDataset.rs
          • NDDataset.rubberband
          • NDDataset.save
          • NDDataset.save_as
          • NDDataset.savgol
          • NDDataset.savgol_filter
          • NDDataset.set_complex
          • NDDataset.set_coordset
          • NDDataset.set_coordtitles
          • NDDataset.set_coordunits
          • NDDataset.set_hypercomplex
          • NDDataset.set_quaternion
          • NDDataset.simps
          • NDDataset.simpson
          • NDDataset.sine
          • NDDataset.sinm
          • NDDataset.smooth
          • NDDataset.snip
          • NDDataset.sort
          • NDDataset.sp
          • NDDataset.squeeze
          • NDDataset.stack
          • 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.trapezoid
          • NDDataset.trapz
          • NDDataset.triang
          • NDDataset.var
          • NDDataset.whittaker
          • NDDataset.write
          • NDDataset.write_csv
          • NDDataset.write_excel
          • NDDataset.write_jcamp
          • NDDataset.write_mat
          • NDDataset.write_matlab
          • NDDataset.write_xls
          • NDDataset.zeros
          • NDDataset.zeros_like
          • NDDataset.zf
          • NDDataset.zf_auto
          • NDDataset.zf_double
          • NDDataset.zf_size
      • 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.copy
          • copy
        • 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
        • 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
        • spectrochempy.set_hypercomplex
          • set_hypercomplex
        • spectrochempy.set_quaternion
          • set_quaternion
      • 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
      • 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.real
          • real
        • spectrochempy.imag
          • imag
        • spectrochempy.RR
          • RR
        • spectrochempy.RI
          • RI
        • spectrochempy.IR
          • IR
        • spectrochempy.II
          • II
        • spectrochempy.component
          • component
        • 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.BaselineCorrector
          • BaselineCorrector
        • 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
          • ht
        • 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
          • spectrochempy.ls
          • spectrochempy.roll
          • spectrochempy.rs
        • Apodization
          • spectrochempy.bartlett
          • spectrochempy.blackmanharris
          • spectrochempy.hamming
          • spectrochempy.general_hamming
          • spectrochempy.hann
          • spectrochempy.triang
          • spectrochempy.em
          • spectrochempy.gm
          • spectrochempy.sp
          • spectrochempy.sine
          • spectrochempy.qsin
          • spectrochempy.sinm
      • Smoothing, filtering, denoising
        • spectrochempy.Filter
          • 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
          • Project.add_datasets
          • Project.add_project
          • Project.add_projects
          • Project.add_script
          • Project.add_scripts
          • Project.copy
          • Project.dump
          • Project.load
          • 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.FileSelector
          • FileSelector
        • spectrochempy.pathclean
          • pathclean
  • Glossary
  • Bibliography
  • Papers citing SpectroChemPy
    • 2024
    • 2023
    • 2022
    • 2021

Contribute

  • Bug reports & feature request
  • Sharing examples & tutorials
  • Developer’s Guide
    • Contributing to SpectroChemPy
      • General Principles
        • Reporting Issues
      • Be prepared to work on the code
        • Version control, Git, and GitHub
        • Installing git
        • Optional: installing a GUI git client
        • Forking the spectrochempy repository
        • Creating a Python development environment
        • Controlling the environments
        • Creating a branch
      • Contributing your changes to SpectroChemPy
        • Commit your code
        • Push your changes
        • Review Your Code
        • Make the pull request (PR)
        • Update your pull request
        • Automatically fix formatting errors
        • Delete your merged branch (optional)
      • Tips for a successful pull request
    • Contributing to the code
      • Code standards
      • Pre-commit
      • Optional dependencies
        • Python (PEP8 / black)
        • Backwards compatibility
      • Testing with continuous integration
      • Test-driven development/code writing
        • Writing tests
        • Using pytest
      • Running the test suite
      • Documenting change log
    • Contributing to specific parts of the code
      • Adding a Reader
        • 1. Add a test and sample files
        • 2. Complete FILETYPES and ALIAS
        • 3. Create the reader_xxx.py file
        • 3. General Guidelines for data and metadata format
        • 4. Polish your code and make the Pull Requests
    • Contributing to the documentation
      • About the spectrochempy documentation
        • SpectroChemPy Docstring Guide
          • About docstrings and standards
          • Writing a docstring
      • Updating a spectrochempy docstring
      • How to build the spectrochempy documentation
        • Requirements
        • Building the documentation
        • Building master branch documentation

Credits

  • Acknowledgments
  • Third-party Licences
  • Citing SpectroChemPy
  • SpectroChempy License
  • Other Licenses
  • See also
SpectroChemPy v0.6.10
  • Adding your examples to the gallery
  • View page source
Previous Next

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 .

Previous Next

© Copyright 2014-2025 - A.Travert & C.Fernandez @ LCS. Last updated on Feb 12, 2025.