spectrochempy.NDDataset¶

class NDDataset(**kwargs)[source]¶

The main N-dimensional dataset class used by SpectroChemPy .

The NDDataset is the main object use by SpectroChemPy. Like numpy ndarrays, NDDataset have the capability to be sliced, sorted and subject to mathematical operations. But, in addition, NDDataset may have units, can be masked and each dimensions can have coordinates also with units. This make NDDataset aware of unit compatibility, e.g., for binary operation such as additions or subtraction or during the application of mathematical operations. In addition or in replacement of numerical data for coordinates, NDDataset can also have labeled coordinates where labels can be different kind of objects (strings, datetime, numpy nd.ndarray or other NDDatasets, etc…).

Parameters

data (array of floats) – Data array contained in the object. The data can be a list, a tuple, a ndarray , a ndarray-like, a NDArray or any subclass of NDArray . Any size or shape of data is accepted. If not given, an empty NDArray will be inited. At the initialisation the provided data will be eventually casted to a numpy-ndarray. If a subclass of NDArray is passed which already contains some mask, labels, or units, these elements will be used to accordingly set those of the created object. If possible, the provided data will not be copied for data input, but will be passed by reference, so you should make a copy of the data before passing them if that’s the desired behavior or set the copy argument to True.
coordset (An instance of |CoordSet| , optional) – coords contains the coordinates for the different dimensions of the data. if coords is provided, it must specified the coord and labels for all dimensions of the data. Multiple coord’s can be specified in an CoordSet instance for each dimension.
coordunits (list, optional) – A list of units corresponding to the dimensions in the order of the coordset.
coordtitles (list, optional) – A list of titles corresponding of the dimensions in the order of the coordset.
**kwargs – Optional keyword parameters (see Other Parameters).

Other Parameters

dtype (str or dtype, optional, default=np.float64) – If specified, the data will be cast to this dtype, else the data will be cast to float64 or complex128.
dims (list of chars, optional) – If specified the list must have a length equal to the number od data dimensions (ndim) and the chars must be taken among x,y,z,u,v,w or t. If not specified, the dimension names are automatically attributed in this order.
name (str, optional) – A user-friendly name for this object. If not given, the automatic id given at the object creation will be used as a name.
labels (array of objects, optional) – Labels for the data. labels can be used only for 1D-datasets. The labels array may have an additional dimension, meaning several series of labels for the same data. The given array can be a list, a tuple, a ndarray , a ndarray-like, a NDArray or any subclass of NDArray .
mask (array of bool or NOMASK, optional) – Mask for the data. The mask array must have the same shape as the data. The given array can be a list, a tuple, or a ndarray . Each values in the array must be False where the data are valid and True when they are not (like in numpy masked arrays). If data is already a MaskedArray, or any array object (such as a NDArray or subclass of it), providing a mask here, will causes the mask from the masked array to be ignored.
units (|Unit| instance or str, optional) – Units of the data. If data is a Quantity then units is set to the unit of the data; if a unit is also explicitly provided an error is raised. Handling of units use the pint package.
timezone (datetime.tzinfo, optional) – The timezone where the data were created. If not specified, the local timezone is assumed.
title (str, optional) – The title of the data dimension. The title attribute should not be confused with the name . The title attribute is used for instance for labelling plots of the data. It is optional but recommended to give a title to each ndarray data.
dlabel (str, optional) – Alias of title.
meta (dict-like object, optional) – Additional metadata for this object. Must be dict-like but no further restriction is placed on meta.
author (str, optional) – Name(s) of the author(s) of this dataset. BNy default, name of the computer note where this dataset is created.
description (str, optional) – An optional description of the nd-dataset. A shorter alias is desc.
origin (str, optional) – Origin of the data: Name of organization, address, telephone number, name of individual contributor, etc., as appropriate.
roi (list) – Region of interest (ROI) limits.
history (str, optional) – A string to add to the object history.
copy (bool, optional) – Perform a copy of the passed object. Default is False.

See also

Coord: Explicit coordinates object.
LinearCoord: Implicit coordinates object.
CoordSet: Set of coordinates.

Notes

The underlying array in a NDDataset object can be accessed through the data attribute, which will return a conventional ndarray .

Methods

`NDDataset.ab`(dataset[, dim])	Alias of `abc`.
`NDDataset.abc`(dataset[, dim])	Automatic baseline correction.
`NDDataset.abs`(dataset[, dtype])	Calculate the absolute value of the given NDDataset element-wise.
`NDDataset.absolute`(dataset[, dtype])	Calculate the absolute value of the given NDDataset element-wise.
`NDDataset.add_coordset`(*coords[, dims])	Add one or a set of coordinates from a dataset.
`NDDataset.align`(dataset, others, *kwargs)	Align individual `NDDataset` along given dimensions using various methods.
`NDDataset.all`(dataset[, dim, keepdims])	Test whether all array elements along a given axis evaluate to True.
`NDDataset.amax`(dataset[, dim, keepdims])	Return the maximum of the dataset or maxima along given dimensions.
`NDDataset.amin`(dataset[, dim, keepdims])	Return the maximum of the dataset or maxima along given dimensions.
`NDDataset.any`(dataset[, dim, keepdims])	Test whether any array element along a given axis evaluates to True.
`NDDataset.arange`([start, stop, step, dtype])	Return evenly spaced values within a given interval.
`NDDataset.argmax`(dataset[, dim])	Indexes of maximum of data along axis.
`NDDataset.argmin`(dataset[, dim])	Indexes of minimum of data along axis.
`NDDataset.around`(dataset[, decimals])	Evenly round to the given number of decimals.
`NDDataset.asfortranarray`()	Make data and mask (ndim >= 1) laid out in Fortran order in memory.
`NDDataset.astype`([dtype])	Cast the data to a specified type.
`NDDataset.autosub`(dataset, ref, *ranges[, ...])	Automatic subtraction of a reference to the dataset.
`NDDataset.average`(dataset[, dim, weights, ...])	Compute the weighted average along the specified axis.
`NDDataset.bartlett`()def bartlett(dataset, ...)	Calculate Bartlett apodization (triangular window with end points at zero).
`NDDataset.basc`(dataset, ranges, *kwargs)	Compute a baseline correction using the BaselineCorrection processor.
`NDDataset.blackmanharris`(...)	Calculate a minimum 4-term Blackman-Harris apodization.
`NDDataset.clip`(dataset[, a_min, a_max])	Clip (limit) the values in a dataset.
`NDDataset.close_figure`()	Close a Matplotlib figure associated to this dataset.
`NDDataset.component`([select])	Take selected components of an hypercomplex array (RRR, RIR, ...).
`NDDataset.concatenate`(datasets, *kwargs)	Concatenation of `NDDataset` objects along a given axis.
`NDDataset.conj`(dataset[, dim])	Conjugate of the NDDataset in the specified dimension.
`NDDataset.conjugate`(dataset[, dim])	Conjugate of the NDDataset in the specified dimension.
`NDDataset.coord`([dim])	Return the coordinates along the given dimension.
`NDDataset.coordmax`(dataset[, dim])	Find coordinates of the maximum of data along axis.
`NDDataset.coordmin`(dataset[, dim])	Find oordinates of the mainimum of data along axis.
`NDDataset.copy`([deep, keepname])	Make a disconnected copy of the current object.
`NDDataset.cs`(dataset[, pts, neg])	Circular shift.
`NDDataset.cumsum`(dataset[, dim, dtype])	Return the cumulative sum of the elements along a given axis.
`NDDataset.dc`(dataset, **kwargs)	Time domain baseline correction.
`NDDataset.delete_coordset`()	Delete all coordinate settings.
`NDDataset.detrend`(dataset[, type, bp])	Remove linear trend along dim from dataset.
`NDDataset.diag`(dataset[, offset])	Extract a diagonal or construct a diagonal array.
`NDDataset.diagonal`(dataset[, offset, dim, dtype])	Return the diagonal of a 2D array.
`NDDataset.dot`(a, b[, strict, out])	Return the dot product of two NDDatasets.
`NDDataset.download_iris`()	Upload the classical "iris" dataset.
`NDDataset.download_nist_ir`(CAS[, index])	Upload IR spectra from NIST webbook
`NDDataset.dump`(filename, **kwargs)	Save the current object into compressed native spectrochempy format.
`NDDataset.em`([lb, shifted, lb, shifted])	Calculate exponential apodization.
`NDDataset.empty`(shape[, dtype])	Return a new `NDDataset` of given shape and type, without initializing entries.
`NDDataset.empty_like`(dataset[, dtype])	Return a new uninitialized `NDDataset` .
`NDDataset.expand_dims`([dim])	Expand the shape of an array.
`NDDataset.eye`(N[, M, k, dtype])	Return a 2-D array with ones on the diagonal and zeros elsewhere.
`NDDataset.fft`(dataset[, size, sizeff, inv, ppm])	Apply a complex fast fourier transform.
`NDDataset.find_peaks`(dataset[, height, ...])	Wrapper and extension of scpy.signal.find_peaks().
`NDDataset.fromfunction`(cls, function[, ...])	Construct a nddataset by executing a function over each coordinate.
`NDDataset.fromiter`(iterable[, dtype, count])	Create a new 1-dimensional array from an iterable object.
`NDDataset.fsh`(dataset, pts, **kwargs)	Frequency shift by Fourier transform.
`NDDataset.fsh2`(dataset, pts, **kwargs)	Frequency Shift by Fourier transform.
`NDDataset.full`(shape[, fill_value, dtype])	Return a new `NDDataset` of given shape and type, filled with `fill_value`.
`NDDataset.full_like`(dataset[, fill_value, dtype])	Return a `NDDataset` of fill_value.
`NDDataset.general_hamming`([alpha])	Calculate generalized Hamming apodization.
`NDDataset.geomspace`(start, stop[, num, ...])	Return numbers spaced evenly on a log scale (a geometric progression).
`NDDataset.get_axis`(args, *kwargs)	Helper function to determine an axis index whatever the syntax used (axis index or dimension names).
`NDDataset.get_labels`([level])	Get the labels at a given level.
`NDDataset.gm`([gb, lb, shifted, gb, lb, shifted])	Calculate lorentz-to-gauss apodization.
`NDDataset.hamming`(dataset, **kwargs)	Calculate generalized Hamming (== Happ-Genzel) apodization.
`NDDataset.hann`(dataset, **kwargs)	Return a Hann window.
`NDDataset.ht`(dataset[, N])	Hilbert transform.
`NDDataset.identity`(n[, dtype])	Return the identity `NDDataset` of a given shape.
`NDDataset.ifft`(dataset[, size])	Apply a inverse fast fourier transform.
`NDDataset.is_units_compatible`(other)	Check the compatibility of units with another object.
`NDDataset.ito`(other[, force])	Inplace scaling to different units.
`NDDataset.ito_base_units`()	Inplace rescaling to base units.
`NDDataset.ito_reduced_units`()	Quantity scaled in place to reduced units, inplace.
`NDDataset.linspace`(cls, start, stop[, num, ...])	Return evenly spaced numbers over a specified interval.
`NDDataset.load`(filename, **kwargs)	Open data from a '*.scp' (NDDataset) or '.pscp' (Project) file.
`NDDataset.logspace`(cls, start, stop[, num, ...])	Return numbers spaced evenly on a log scale.
`NDDataset.ls`(dataset[, pts])	Left shift and zero fill.
`NDDataset.max`(dataset[, dim, keepdims])	Return the maximum of the dataset or maxima along given dimensions.
`NDDataset.mc`(dataset)	Modulus calculation.
`NDDataset.mean`(dataset[, dim, dtype, keepdims])	Compute the arithmetic mean along the specified axis.
`NDDataset.min`(dataset[, dim, keepdims])	Return the maximum of the dataset or maxima along given dimensions.
`NDDataset.ones`(shape[, dtype])	Return a new `NDDataset` of given shape and type, filled with ones.
`NDDataset.ones_like`(dataset[, dtype])	Return `NDDataset` of ones.
`NDDataset.pipe`(func, args, *kwargs)	Apply func(self, args, *kwargs).
`NDDataset.pk`(dataset[, phc0, phc1, exptc, pivot])	Linear phase correction.
`NDDataset.pk_exp`(dataset[, phc0, pivot, exptc])	Exponential Phase Correction.
`NDDataset.plot`([method])	Generic plot function.
`NDDataset.plot_1D`(...[, method])	Plot of one-dimensional data.
`NDDataset.plot_2D`(...[, method])	Plot of 2D array.
`NDDataset.plot_3D`(...[, method])	Plot of 2D array as 3D plot
`NDDataset.plot_bar`(dataset, args, *kwargs)	Plot a 1D dataset with bars.
`NDDataset.plot_image`(dataset, args, *kwargs)	Plot a 2D dataset as an image plot.
`NDDataset.plot_map`(dataset, args, *kwargs)	Plot a 2D dataset as a contoured map.
`NDDataset.plot_multiple`(datasets[, method, ...])	Plot a series of 1D datasets as a scatter plot with optional lines between markers.
`NDDataset.plot_pen`(dataset, args, *kwargs)	Plot a 1D dataset with solid pen by default.
`NDDataset.plot_scatter`(dataset, args, *kwargs)	Plot a 1D dataset as a scatter plot (points can be added on lines).
`NDDataset.plot_scatter_pen`(dataset, *args, ...)	Plot a 1D dataset with solid pen by default.
`NDDataset.plot_stack`(dataset, args, *kwargs)	Plot a 2D dataset as a stack plot.
`NDDataset.plot_surface`(dataset, args, *kwargs)	Plot a 2D dataset as a a 3D-surface.
`NDDataset.plot_waterfall`(dataset, *args, ...)	Plot a 2D dataset as a a 3D-waterfall plot.
`NDDataset.ps`(dataset)	Power spectrum.
`NDDataset.ptp`(dataset[, dim, keepdims])	Range of values (maximum - minimum) along a dimension.
`NDDataset.qsin`(dataset[, ssb])	Equivalent to `sp`, with pow = 2 (squared sine bell apodization window).
`NDDataset.random`([size, dtype])	Return random floats in the half-open interval [0.0, 1.0).
`NDDataset.read`(paths, *kwargs)	Generic read method.
`NDDataset.read_carroucell`([directory])	Open .spa files in a directory after a carroucell experiment.
`NDDataset.read_csv`(paths, *kwargs)	Open a .csv file or a list of .csv files.
`NDDataset.read_ddr`(paths, *kwargs)	Open a Surface Optics Corps.
`NDDataset.read_dir`([directory])	Read an entire directory.
`NDDataset.read_hdr`(paths, *kwargs)	Open a Surface Optics Corps.
`NDDataset.read_jcamp`(paths, *kwargs)	Open Infrared JCAMP-DX files with extension `.jdx` or `.dx`.
`NDDataset.read_labspec`(paths, *kwargs)	Read a single Raman spectrum or a series of Raman spectra.
`NDDataset.read_mat`(paths, *kwargs)	Read a matlab file with extension `.mat` and return its content as a list.
`NDDataset.read_matlab`(paths, *kwargs)	Read a matlab file with extension `.mat` and return its content as a list.
`NDDataset.read_omnic`(paths, *kwargs)	Open a Thermo Nicolet OMNIC file.
`NDDataset.read_opus`(paths, *kwargs)	Open Bruker OPUS file(s).
`NDDataset.read_quadera`(paths, *kwargs)	Read a Pfeiffer Vacuum's QUADERA® mass spectrometer software file with extension `.asc`.
`NDDataset.read_remote`(file_or_dir, **kwargs)	Download and read files or an entire directory on github spectrochempy_data repository.
`NDDataset.read_sdr`(paths, *kwargs)	Open a Surface Optics Corps.
`NDDataset.read_soc`(paths, *kwargs)	Open a Surface Optics Corps.
`NDDataset.read_spa`(paths, *kwargs)	Open a Thermo Nicolet file or a list of files with extension `.spa`.
`NDDataset.read_spc`(paths, *kwargs)	Open a Thermo Nicolet file or a list of files with extension `.spg`.
`NDDataset.read_spg`(paths, *kwargs)	Open a Thermo Nicolet file or a list of files with extension `.spg`.
`NDDataset.read_srs`(paths, *kwargs)	Open a Thermo Nicolet file or a list of files with extension `.srs`.
`NDDataset.read_topspin`(paths, *kwargs)	Open Bruker TOPSPIN (NMR) dataset.
`NDDataset.read_zip`(paths, *kwargs)	Open a zipped list of data files.
`NDDataset.remove_masks`()	Remove all masks previously set on this array.
`NDDataset.roll`(dataset[, pts, neg])	Roll dimensions.
`NDDataset.round`(dataset[, decimals])	Evenly round to the given number of decimals.
`NDDataset.round_`(dataset[, decimals])	Evenly round to the given number of decimals.
`NDDataset.rs`(dataset[, pts])	Right shift and zero fill.
`NDDataset.save`(**kwargs)	Save the current object in SpectroChemPy format.
`NDDataset.save_as`([filename])	Save the current `NDDataset` in SpectroChemPy format (*.scp).
`NDDataset.savgol_filter`(dataset[, ...])	Apply a Savitzky-Golay filter to a NDDataset.
`NDDataset.set_complex`([inplace])	Set the object data as complex.
`NDDataset.set_coordset`(args, *kwargs)	Set one or more coordinates at once.
`NDDataset.set_coordtitles`(args, *kwargs)	Set titles of the one or more coordinates.
`NDDataset.set_coordunits`(args, *kwargs)	Set units of the one or more coordinates.
`NDDataset.set_hypercomplex`([inplace])	Alias of set_quaternion.
`NDDataset.set_quaternion`([inplace])	Alias of set_quaternion.
`NDDataset.simpson`(dataset, args, *kwargs)	Integrate using the composite Simpson's rule.
`NDDataset.sine`(dataset, args, *kwargs)	Strictly equivalent to `sp`.
`NDDataset.sinm`(dataset[, ssb])	Equivalent to `sp`, with pow = 1 (sine bell apodization window).
`NDDataset.smooth`(dataset[, window_length, ...])	Smooth the data using a window with requested size.
`NDDataset.sort`(**kwargs)	Return the dataset sorted along a given dimension.
`NDDataset.sp`([ssb, pow, ssb, pow])	Calculate apodization with a Sine window multiplication.
`NDDataset.squeeze`(*dims[, inplace])	Remove single-dimensional entries from the shape of a NDDataset.
`NDDataset.stack`(*datasets)	Stack of `NDDataset` objects along a new dimension.
`NDDataset.std`(dataset[, dim, dtype, ddof, ...])	Compute the standard deviation along the specified axis.
`NDDataset.sum`(dataset[, dim, dtype, keepdims])	Sum of array elements over a given axis.
`NDDataset.swapaxes`(dim1, dim2[, inplace])	Alias of `swapdims`.
`NDDataset.swapdims`(dim1, dim2[, inplace])	Interchange two dimensions of a NDDataset.
`NDDataset.take`(indices, **kwargs)	Take elements from an array.
`NDDataset.to`(other[, inplace, force])	Return the object with data rescaled to different units.
`NDDataset.to_array`()	Return a numpy masked array.
`NDDataset.to_base_units`([inplace])	Return an array rescaled to base units.
`NDDataset.to_reduced_units`([inplace])	Return an array scaled in place to reduced units.
`NDDataset.to_xarray`()	Convert a NDDataset instance to an `DataArray` object.
`NDDataset.transpose`(*dims[, inplace])	Permute the dimensions of a NDDataset.
`NDDataset.trapezoid`(dataset, **kwargs)	Integrate using the composite trapezoidal rule.
`NDDataset.trapz`(args, *kwargs)	An alias of `trapezoid` kept for backwards compatibility.
`NDDataset.triang`()def triang(dataset, **kwargs)	Calculate triangular apodization with non-null extremities and maximum value normalized to 1.
`NDDataset.var`(dataset[, dim, dtype, ddof, ...])	Compute the variance along the specified axis.
`NDDataset.write`(dataset[, filename])	Write the current dataset.
`NDDataset.write_csv`(args, *kwargs)	Write a dataset in CSV format.
`NDDataset.write_excel`(args, *kwargs)	This method is an alias of `write_excel`.
`NDDataset.write_jcamp`(args, *kwargs)	This method is an alias of `write_jcamp`.
`NDDataset.write_jdx`(args, *kwargs)	This method is an alias of `write_jcamp`.
`NDDataset.write_mat`(args, *kwargs)	This method is an alias of `write_matlab`.
`NDDataset.write_matlab`(args, *kwargs)	This method is an alias of `write_matlab`.
`NDDataset.write_xls`(args, *kwargs)	This method is an alias of `write_excel`.
`NDDataset.zeros`(shape[, dtype])	Return a new `NDDataset` of given shape and type, filled with zeros.
`NDDataset.zeros_like`(dataset[, dtype])	Return a `NDDataset` of zeros.
`NDDataset.zf`(dataset[, size, mid])	Zero fill to given size.
`NDDataset.zf_auto`(dataset[, mid])	Zero fill to next largest power of two.
`NDDataset.zf_double`(dataset, n[, mid])	Zero fill by doubling original data size once or multiple times.
`NDDataset.zf_size`(dataset[, size, mid])	Zero fill to given size.

Attributes

`NDDataset.II`	The array with imaginary-imaginary component of hypercomplex 2D data.
`NDDataset.IR`	The array with imaginary-real component of hypercomplex 2D `data`.
`NDDataset.RI`	The array with real-imaginary component of hypercomplex 2D `data`.
`NDDataset.RR`	The array with real component in both dimension of hypercomplex 2D `data`.
`NDDataset.T`	Transposed `NDDataset` .
`NDDataset.author`	Creator of the dataset (str).
`NDDataset.ax`	The main matplotlib axe associated to this dataset.
`NDDataset.axT`	The matplotlib axe associated to the transposed dataset.
`NDDataset.axec`	Matplotlib colorbar axe associated to this dataset.
`NDDataset.axecT`	Matplotlib colorbar axe associated to the transposed dataset.
`NDDataset.axex`	Matplotlib projection x axe associated to this dataset.
`NDDataset.axey`	Matplotlib projection y axe associated to this dataset.
`NDDataset.comment`	Provides a comment (Alias to the description attribute).
`NDDataset.coordnames`	List of the `Coord` names.
`NDDataset.coordset`	`CoordSet` instance.
`NDDataset.coordtitles`	List of the `Coord` titles.
`NDDataset.coordunits`	List of the `Coord` units.
`NDDataset.created`	Creation date object (Datetime).
`NDDataset.data`	The `data` array.
`NDDataset.description`	Provides a description of the underlying data (str).
`NDDataset.dimensionless`	True if the `data` array is dimensionless - Readonly property (bool).
`NDDataset.dims`	Names of the dimensions (list).
`NDDataset.directory`	Current directory for this dataset.
`NDDataset.divider`	Matplotlib plot divider.
`NDDataset.dtype`	Data type (np.dtype).
`NDDataset.fig`	Matplotlib figure associated to this dataset.
`NDDataset.fignum`	Matplotlib figure associated to this dataset.
`NDDataset.filename`	Current filename for this dataset.
`NDDataset.filetype`	Type of current file.
`NDDataset.has_complex_dims`	True if at least one of the `data` array dimension is complex.
`NDDataset.has_data`	True if the `data` array is not empty and size > 0.
`NDDataset.has_defined_name`	True is the name has been defined (bool).
`NDDataset.has_units`	True if the `data` array have units - Readonly property (bool).
`NDDataset.history`	Describes the history of actions made on this array (tr.List of strings).
`NDDataset.id`	Object identifier - Readonly property (str).
`NDDataset.imag`	The array with imaginary component of the `data`.
`NDDataset.is_1d`	True if the `data` array has only one dimension (bool).
`NDDataset.is_complex`	True if the 'data' are complex (Readonly property).
`NDDataset.is_empty`	True if the `data` array is empty or size=0, and if no label are present.
`NDDataset.is_float`	True if the `data` are real values - Readonly property (bool).
`NDDataset.is_integer`	True if the `data` are integer values - Readonly property (bool).
`NDDataset.is_interleaved`	True if the `data` array is hypercomplex with interleaved data.
`NDDataset.is_labeled`	True if the `data` array have labels - Readonly property (bool).
`NDDataset.is_masked`	True if the `data` array has masked values.
`NDDataset.is_quaternion`	True if the `data` array is hypercomplex .
`NDDataset.labels`	An array of labels for `data` (`ndarray` of str).
`NDDataset.limits`	Range of the data.
`NDDataset.local_timezone`	Return the local timezone.
`NDDataset.m`	The `data` array (`ndarray`).
`NDDataset.magnitude`	The `data` array (`ndarray`).
`NDDataset.mask`	Mask for the data (`ndarray` of bool).
`NDDataset.masked_data`	The actual masked `data` array - Readonly property (`array`).
`NDDataset.meta`	Additional metadata (`Meta`).
`NDDataset.modeldata`	`ndarray` - models data.
`NDDataset.modified`	Date of modification (readonly property).
`NDDataset.name`	A user-friendly name (str).
`NDDataset.ndaxes`	A dictionary containing all the axes of the current figures.
`NDDataset.ndim`	The number of dimensions of the `data` array (Readonly property).
`NDDataset.origin`	Origin of the data.
`NDDataset.parent`	`Project` instance.
`NDDataset.preferences`	`Meta` instance object - Additional metadata.
`NDDataset.real`	The array with real component of the `data`.
`NDDataset.roi`	Region of interest (ROI) limits (list).
`NDDataset.shape`	A tuple with the size of each dimension - Readonly property.
`NDDataset.size`	Size of the underlying `data` array - Readonly property (int).
`NDDataset.suffix`	Filename suffix.
`NDDataset.timezone`	Return the timezone information.
`NDDataset.title`	An user friendly title (str).
`NDDataset.umasked_data`	The actual array with mask and unit (`Quantity`).
`NDDataset.unitless`	`bool` - True if the `data` does not have `units` (Readonly property).
`NDDataset.units`	`Unit` - The units of the data.
`NDDataset.value`	Alias of `values`.
`NDDataset.values`	`Quantity` - The actual values (data, units) contained in this object (Readonly property).

II¶

The array with imaginary-imaginary component of hypercomplex 2D data.

(Readonly property).

IR¶

The array with imaginary-real component of hypercomplex 2D data.

(Readonly property).

RI¶

The array with real-imaginary component of hypercomplex 2D data.

(Readonly property).

RR¶

The array with real component in both dimension of hypercomplex 2D data.

This readonly property is equivalent to the real property.

T¶

Transposed NDDataset .

The same object is returned if ndim is less than 2.

author¶: Creator of the dataset (str).

ax¶: The main matplotlib axe associated to this dataset.

axT¶: The matplotlib axe associated to the transposed dataset.

axec¶: Matplotlib colorbar axe associated to this dataset.

axecT¶: Matplotlib colorbar axe associated to the transposed dataset.

axex¶: Matplotlib projection x axe associated to this dataset.

axey¶: Matplotlib projection y axe associated to this dataset.

comment¶: Provides a comment (Alias to the description attribute).

coordnames¶

List of the Coord names.

Read only property.

coordset¶

CoordSet instance.

Contains the coordinates of the various dimensions of the dataset. It’s a readonly property. Use set_coords to change one or more coordinates at once.

coordtitles¶

List of the Coord titles.

Read only property. Use set_coordtitle to eventually set titles.

coordunits¶

List of the Coord units.

Read only property. Use set_coordunits to eventually set units.