Welcome to smoothy’s documentation!

Core functions

Note

For Developers and Advanced Users

Functions used by UPI.

Data Analysis

smoothy.core.analysis.denoise(data, threshold)[source]

Performs denoising of data cube, thresholding over the threshold value.

Parameters:

data : numpy.ndarray or astropy.nddata.NDData or or astropy.nddata.NDData

Astronomical data cube.

threshold : float

Threshold value used for denoising.
Returns:

result : numpy.ndarray

Denoised (thresholded) astronomical data cube.
smoothy.core.analysis.gaussian_function(mu, P, feat, peak)[source]

Generates an N-dimensional Gaussian using the feature matrix feat, centered at mu, with precision matrix P and with intensity peak.

Parameters:

mu : numpy.ndarray

Centers of gaussians array.

P : numpy.ndarray

Precision matrix.

feat : numpy.ndarray.

Features matrix.

peak : float

Peak value of the resulting evaluation.
Returns:

result: 2D numpy.ndarray

Returns the gaussian function evaluated at the value on feat.
smoothy.core.analysis.integrate(data, mask=None, axis=0)[source]

Sums the slices of a cube of data given an axis.

Parameters:

data : (M,N,Z) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

Astronomical data cube.

mask : numpy.ndarray (default = None)

axis : int (default=(0))
Returns:

A numpy array with the integration results.
smoothy.core.analysis.rms(data, mask=None)[source]

Compute the RMS of data. If mask != None, then we use that mask.

Parameters:

data : (M,N,Z) numpy.ndarray or astropy.nddata.NDData or or astropy.nddata.NDDataRef

Astronomical data cube.

mask : numpy.ndarray (default = None)
Returns:

RMS of the data (float)

Utils

smoothy.core.utilities.add(data, flux, lower, upper)[source]

Adds flux to a sub-cube of an astronomical data cube.

Parameters:

data : numpy.ndarray or astropy.nddata.NDData or or astropy.nddata.NDData

Astronomical data cube.

flux : numpy.ndarray

Flux added to the cube.

lower : tuple

Lower bound of the sub-cube to which flux will be added.

upper : tuple

Upper bound of the sub-cube to which flux will be added.
smoothy.core.utilities.fix_limits(data, vect)[source]

Fix vect index to be inside data

Parameters:

data : numpy.ndarray or numpy.ma.MaskedArray

Astronomical data cube.

vect : tuple, list or numpy.ndarray

Array with the indexes to be fixed.
Returns:

result : numpy.ndarray

Fixed array of indexes.
smoothy.core.utilities.fix_mask(data, mask)[source]
Parameters:

data : numpy.ndarray or numpy.ma.MaskedArray

Astronomical data cube.

mask : numpy.ndarray

Boolean that will be applied.
Returns:

result : numpy.ma.MaskedArray

Masked astronomical data cube.
smoothy.core.utilities.index_features(data, lower=None, upper=None)[source]

Creates an array with indices in features format

smoothy.core.utilities.matching_slabs(data, flux, lower, upper)[source]

Obtain the matching subcube inside the lower and upper points.

Parameters:

data : numpy.ndarray

First data cube

flux : numpy.ndarray

Second data cubse

lower : tuple

Lower coordinates for the subcube.

upper : tuple

Upper coordinates for the subcube.
Returns:

The subcube inside the lower and upper points that matches both data cube dimensions.
smoothy.core.utilities.slab(data, lower=None, upper=None)[source]

Obtain the n-dimensional slab from lower to upper (i.e. slab is a vector of slices)

Parameters:

data : numpy.ndarray

Atronomical data cube.

lower : 3-tuple (default=None)

Lower coordinates for the subcube.

upper : 3-tuple (default=None)

Upper coordinates for the subcube.
Returns:

result : list

list of slices using lower and upper coordinates to create a subcube.
smoothy.core.utilities.standarize(data)[source]

Standarize astronomical data cubes in the 0-1 range.

Parameters:

data : numpy.ndarray or astropy.nddata.NDData or or astropy.nddata.NDData

Astronomical data cube.
Returns:

result : tuple

Tuple containing the standarized numpy.ndarray or astropy.nddata.NDData cube, the factor scale y_fact and the shift y_min.
smoothy.core.utilities.unstandarize(data, a, b)[source]

Unstandarize the astronomical data cube: \(a \cdot data + b\).

Parameters:

data : numpy.ndarray or astropy.nddata.NDData or or astropy.nddata.NDData

Astronomical data cube.

a : float

Scale value.

b : float

Shift value.
Returns:

result : numpy.ndarray or astropy.nddata.NDData

Unstandarized astronomical cube.

Input-Output (IO)

Visualization Functions

smoothy.io.graph.visualize(data, wcs=None, unit=None, contour=False)[source]

Generic function to visualize data, line-plot for 1D and image for 2D.

Parameters:

data : numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

Astronomical image

wcs : astropy.wcs.WCS

World Coordinate System from the image (not needed if contained in NDData)

unit : astropy.unit

Image units (not needed if contained in NDData)

contour : numpy.ndarray

For plotting Contourns
smoothy.io.graph.visualize_image(data, wcs=None, unit=None, contour=False)[source]

Plot 2D astronomical data.

Parameters:

data : numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

Astronomical image

wcs : astropy.wcs.WCS

World Coordinate System from the image (not needed if contained in NDData)

unit : astropy.unit

Image units (not needed if contained in NDData)

contour : numpy.ndarray

For plotting Contourns
smoothy.io.graph.visualize_plot(data, wcs=None, unit=None)[source]

Plot 1D data for astronomical data.

Parameters:

data : numpy.ndarray or astropy.nddata.NDData

Astronomical image

wcs : astropy.wcs.WCS

World Coordinate System from the image (not needed if contained in NDData)

unit : astropy.unit

Image units (not needed if contained in NDData)
smoothy.io.graph.visualize_spectra(data, wcs=None, unit=None, velocities=False)[source]

Plot spectra from astronomical data.

Parameters:

data : numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

Astronomical data

wcs : astropy.wcs.WCS

World Coordinate System from the image (not needed if contained in NDData)

unit : astropy.unit

Image units (not needed if contained in NDData)

velocities: bool

Use spectral velocities
smoothy.io.graph.visualize_volume(data, wcs=None, unit=None)[source]

Plot 3D astronomical data.

Parameters:

data : numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

Astronomical cube

wcs : astropy.wcs.WCS

World Coordinate System from the image (not needed if contained in NDData)

unit : astropy.unit

Image units (not needed if contained in NDData)

FITS handling functions

smoothy.io.fits.Data_to_HDU(cube, primary=False)[source]

Create a HDU object from an N-dimensional dataset.

Parameters:

cube : numpy.ndarray or astropy.nddata.NDData or or astropy.nddata.NDDataRef

Astronomical data cube.

primary : bool

Whether to pick the primary or an image HDU.
Returns:

result: HDU object with data from the data cube.
smoothy.io.fits.HDU_to_Data(hdu)[source]

Create an N-dimensional dataset from an HDU component.

Parameters:

hdu : HDU object

HDU to transform into an N-dimensional dataset.
Returns:

result: astropy.nddata.NDDataRef with data from the HDU object.
smoothy.io.fits.HDU_to_Table(hdu)[source]

Create a data table from a HDU component.

Parameters:

hdu : HDU object

HDU to transform into a data table.
Returns:

result: astropy.table.Table with data from the HDU.
smoothy.io.fits.Table_to_HDU(tab)[source]

Create a HDU object from a data table.

Parameters:

tab : astropy.table.Table

Table to transform into a HDU object.
Returns:

result: HDU object with data from the data table.
smoothy.io.fits.load_fits(filePath, primary=False)[source]

Loads a FITS file and converts it into an N-Dimensional Dataset.

Parameters:

filepath : path of the FITS file.

primary : bool

if True it gets only primmary data-cube.
Returns:

Primary NDData image or astropy table, and/or:

N-Dimensional Datasets and Astropy Tables lists

User Programmatic Interface (UPI)

Functions to simplificate the programming task for standard users.

Axes Manipulation

smoothy.upi.axes.axes_names(data, wcs=None)[source]

Get the axes’s names.

Parameters:

data : (M,N) or (M,N,Z) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

Astronomical data cube.

wcs : astropy.wcs.wcs.WCS

World Coordinate System to use.
Returns:

result: numpy.ndarray

Numpy ndarray with the axes’s names from the WCS.
smoothy.upi.axes.axes_units(data, wcs=None)[source]

Get units of the axes

Parameters:

data : (M,N) or (M,N,Z) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

Astronomical data cube.

wcs : astropy.wcs.wcs.WCS

World Coordinate System to use.
Returns:

result: (M,N) or (M,N,Z) numpy.ndarray

Vector with the units of the axes
smoothy.upi.axes.center(data, wcs=None)[source]

Get center of the data

Parameters:

data : (M,N) or (M,N,Z) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

Astronomical data cube.

wcs : astropy.wcs.wcs.WCS

World Coordinate System to use.
Returns:

result: astropy.units.quantity.Quantity

Center of the data
smoothy.upi.axes.extent(data, wcs=None, region=None)[source]

Get the axes extent.

Parameters:

data : (M,N) or (M,N,Z) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

Astronomical data cube.

wcs : astropy.wcs.wcs.WCS

World Coordinate System to use.

region :(lower : (M,N) or (M,N,Z), upper

Start and End index in data (int tuples)
Returns:

result: (M, N) tuple of astropy.units.quantity.Quantity

Axes extent
smoothy.upi.axes.features(data, wcs=None, region=None)[source]

Creates an array with WCS axes in features format

Parameters:

data : (M,N) or (M,N,Z) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

Astronomical data cube.

wcs : astropy.wcs.wcs.WCS

World Coordinate System to use.

region :(lower : (M,N) or (M,N,Z), upper

Start and End index in data (int tuples)
Returns:

result: astropy.table.Table

Table with WCS information of a section from the data.
smoothy.upi.axes.opening(data, center, window, wcs=None)[source]

Field of view (center +- window) converted to indices

Parameters:

data : (M,N) or (M,N,Z) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

Astronomical data cube.

center : astropy.units.quantity.Quantity

Center of the field of view in WCS.

window : astropy.units.quantity.Quantity

Window for the field in WCS.

wcs : astropy.wcs.wcs.WCS

World Coordinate System to use.

Returns

——-

result: ((M1,N1,Z1),(M2,N2,Z2)) tuple of tuple of ints
smoothy.upi.axes.resolution(data, wcs=None)[source]

Get the resolution of data

Parameters:

data : (M,N) or (M,N,Z) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

Astronomical data cube.

wcs : astropy.wcs.wcs.WCS

World Coordinate System to use.
Returns:

result: (M,N) or (M,N,Z) numpy.ndarray

Resolution of the data
smoothy.upi.axes.spectral_velocities(data, wcs=None, fqs=None, fqis=None, restfrq=None)[source]

Get the spectral velocities from frequencies fqs given a rest frequency (by default search for it in the WCS). If fqs is None, then frequencies indices (fqis) need to be given.

Parameters:

data : (M,N) or (M,N,Z) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

Astronomical data cube.

wcs : astropy.wcs.wcs.WCS

World Coordinate System to use.

fqs : astropy.units.quantity.Quantity

Array of frequencies with units.

fqis : list of integers

Array of frequencies indices

restfrq : astropy.units.quantity.Quantity

Rest frequency
Returns:

result: astropy.units.quantity.Quantity

Array of Spectral velocities.

Data Manipulation

class smoothy.upi.data.Data(data, uncertainty=None, mask=None, wcs=None, meta=None, unit=None, copy=False)[source]

A generic represenation of astronomical n-dimensional data array. Extends NDData.

axes_names()[source]

Get the axes’s names.

Returns:

result: numpy.ndarray

Numpy ndarray with the axes’s names from the WCS.
axes_units()[source]

Get units of the axes

Returns:

result: (M,N) or (M,N,Z) numpy.ndarray

Vector with the units of the axes
center()[source]

Get center of the data

Returns:

result: astropy.units.quantity.Quantity

Center of the data
extent(region=None)[source]

Get the axes extent.

Parameters:

region :(lower : (M,N) or (M,N,Z), upper

Start and End index in data (int tuples)
Returns:

result: (M, N) tuple of astropy.units.quantity.Quantity

Axes extent
features(region=None)[source]

Creates an array with WCS axea in features format

Parameters:

region :(lower : (M,N) or (M,N,Z), upper

Start and End index in data (int tuples)
Returns:

result: astropy.table.Table

Table with WCS information of a section from the data.
opening(center, window)[source]

Field of view (center +- window) converted to indices

Parameters:

center : astropy.units.quantity.Quantity

Center of the field of view in WCS.

window : astropy.units.quantity.Quantity

Window for the field in WCS.
Returns:

result: ((M1,N1,Z1),(M2,N2,Z2)) tuple of tuple of ints
resolution()[source]

Get the resolution of data

Returns:

result: (M,N) or (M,N,Z) numpy.ndarray

Resolution of the data
spectral_velocities(fqs=None, fqis=None, restfrq=None)[source]

Get the spectral velocities from frequencies fqs given a rest frequency (by default search for it in the WCS). If fqs is None, then frequencies indices (fqis) need to be given.

Parameters:

fqs : astropy.units.quantity.Quantity

Array of frequencies with units.

fqis : list of integers

Array of frequencies indices

restfrq : astropy.units.quantity.Quantity

Rest frequency
Returns:

result: astropy.units.quantity.Quantity

Array of Spectral velocities.

Flux Manipulation

smoothy.upi.flux.add(data, flux, lower=None, upper=None, wcs=None, unit=None, meta=None, mask=None)[source]

Create a new data with the new flux added.

Lower and upper are bounds for data. This operation is border-safe and creates a new object at each call.

Parameters:

data : (M,N) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

flux : float

Flux of data

lower : numpy.ndarray

upper : numpy.ndarray

Bounds for data

wcs : World Coordinate System data (http://docs.astropy.org/en/stable/wcs/)

mask : numpy.ndarray

mask for the data

unit : astropy.units.Unit

meta : FITS metadata
Returns:

NDDataRef: structure with new flux added
smoothy.upi.flux.denoise(data, wcs=None, mask=None, unit=None, threshold=0.0)[source]

Simple denoising given a threshold (creates a new object)

Parameters:

data : (M,N) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

wcs : World Coordinate System data (http://docs.astropy.org/en/stable/wcs/)

mask : numpy.ndarray

mask for the data

unit : astropy.units.Unit

threshold : float
Returns:

NDDataRef: Data denoised
smoothy.upi.flux.noise_level(data, mask=None, unit=None)[source]

Compute the RMS of data.

Parameters:

data : (M,N) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

mask : numpy.ndarray

mask for the data

unit : astropy.units.Unit
Returns:

rms : float

RMS of data
smoothy.upi.flux.standarize(data, wcs=None, unit=None, mask=None, meta=None)[source]

Standarize data:

Parameters:

data : (M,N) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

wcs : World Coordinate System data (http://docs.astropy.org/en/stable/wcs/)

mask : numpy.ndarray

mask for the data

unit : astropy.units.Unit

meta : FITS metadata
Returns:

Standarized data where data = a * res + b
smoothy.upi.flux.unstandarize(data, a, b, wcs=None, unit=None, mask=None, meta=None)[source]

Unstandarize data: res = a * data + b

Parameters:

data : (M,N) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

a : float

slope of straight

b : float

Intercept of straight

wcs : World Coordinate System data (http://docs.astropy.org/en/stable/wcs/)

mask : numpy.ndarray

mask for the data

unit : astropy.units.Unit

meta : FITS metadata
Returns:

NDDataRef: Unstandarized data: res = a * data + b
smoothy.upi.flux.world_gaussian(data, mu, P, peak, cutoff, wcs=None)[source]

Creates a gaussian flux at mu position (WCS), with P shape, with a maximum value equal to peak, and with compact support up to the cutoff contour

Parameters:

data : (M,N) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

mu : float

P : tuple

Shape of result

peak : float

maximum value

cutoff :

wcs : World Coordinate System data (http://docs.astropy.org/en/stable/wcs/)
Returns:

Tuple of gaussian flux and borders

Data Statistics

smoothy.upi.reduction.moment0(data, wcs=None, mask=None, unit=None, restfrq=None)[source]

Calculate moment 0 from a data cube.

Parameters:

data : (M,N,Z) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

Astronomical data cube.

wcs : astropy.wcs.wcs.WCS

World Coordinate System to use.

mask : numpy.ndarray

Mask for data.

unit : astropy.units.Unit

restfrq : astropy.units.quantity.Quantity

Rest frequency
Returns:

result: astropy.nddata.NDDataRef

Moment 0 of the data cube
smoothy.upi.reduction.moment1(data, wcs=None, mask=None, unit=None, restfrq=None)[source]

Calculate moment 1 from a data cube.

Parameters:

data : (M,N,Z) numpy.ndarray or astropy.nddata.NDData

Astronomical data cube.

wcs : astropy.wcs.wcs.WCS

World Coordinate System to use

mask : numpy.ndarray

Mask for data.

unit : astropy.units.Unit

restfrq : astropy.units.quantity.Quantity

Rest frequency
Returns:

result: astropy.nddata.NDData

Moment 1 of the data cube
smoothy.upi.reduction.moment2(data, wcs=None, mask=None, unit=None, restfrq=None)[source]

Calculate moment 2 from a data cube.

Parameters:

data : (M,N,Z) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

Astronomical data cube.

wcs : astropy.wcs.wcs.WCS

World Coordinate System to use

mask : numpy.ndarray

Mask for data.

unit : astropy.units.Unit

restfrq : astropy.units.quantity.Quantity

Rest frequency
Returns:

result: astropy.nddata.NDDataRef

Moment 2 of the data cube
smoothy.upi.reduction.spectra(data, wcs=None, mask=None, unit=None, restrict=None)[source]
Parameters:

data : (M,N,Z) numpy.ndarray or astropy.nddata.NDData or astropy.nddata.NDDataRef

Astronomical data cube.

wcs : astropy.wcs.wcs.WCS

World Coordinate System to use

mask : numpy.ndarray

Mask for data.

unit : astropy.units.Unit

restrict : boolean
Returns:

result: astropy.nddata.NDData

Moment 2 of the data cube

Formatting

Indices and tables