Spectrum¶

class
mpdaf.obj.
Spectrum
(filename=None, hdulist=None, data=None, mask=False, var=None, ext=None, unit=Unit(dimensionless), copy=True, dtype=None, primary_header=None, data_header=None, **kwargs)[source]¶ Bases:
mpdaf.obj.arithmetic.ArithmeticMixin
,mpdaf.obj.DataArray
Spectrum objects contain 1D arrays of numbers, optionally accompanied by corresponding variances. These numbers represent sample fluxes along a regularly spaced grid of wavelengths.
The spectral pixel values and their variances, if any, are available as arrays[q that can be accessed via properties of the Spectrum object called .data and .var, respectively. These arrays are usually masked arrays, which share a boolean masking array that can be accessed via a property called .mask. In principle, these arrays can also be normal numpy arrays without masks, in which case the .mask property holds the value, numpy.ma.nomask. However nonmasked arrays are only supported by a subset of mpdaf functions at this time, so masked arrays should be used where possible.
When a new Spectrum object is created, the data, variance and mask arrays can either be specified as arguments, or the name of a FITS file can be provided to load them from.
Parameters: filename : string
An optional FITS file name from which to load the spectrum. None by default. This argument is ignored if the data argument is not None.
ext : int or (int,int) or string or (string,string)
The optional number/name of the data extension or the numbers/names of the data and variance extensions.
wave :
mpdaf.obj.WaveCoord
The wavelength coordinates of the spectrum.
unit : str or
astropy.units.Unit
The physical units of the data values. Defaults to
astropy.units.dimensionless_unscaled
.data : float array
An optional 1 dimensional array containing the values of each pixel of the spectrum, stored in ascending order of wavelength (None by default). Where given, this array should be 1 dimensional.
var : float array
An optional 1 dimensional array containing the estimated variances of each pixel of the spectrum, stored in ascending order of wavelength (None by default).
Attributes
filename (string) The name of the originating FITS file, if any. Otherwise None. unit ( astropy.units.Unit
) The physical units of the data values.primary_header ( astropy.io.fits.Header
) The FITS primary header instance, if a FITS file was provided.data_header ( astropy.io.fits.Header
) The FITS header of the DATA extension.wave ( mpdaf.obj.WaveCoord
) The wavelength coordinates of the spectrum.Attributes Summary
data
Return data as a numpy.ma.MaskedArray
.dtype
The type of the data. mask
The shared masking array of the data and variance arrays. ndim
The number of dimensions in the data and variance arrays : int shape
The lengths of each of the data axes. var
Return variance as a numpy.ma.MaskedArray
.Methods Summary
LSF_convolve
(lsf, size, **kwargs)Convolve spectrum with LSF. abmag_band
(lbda, dlbda)Compute AB magnitude corresponding to the wavelength band. abmag_filter
(lbda, eff)Compute AB magnitude using array filter. abmag_filter_name
(name)Compute AB magnitude using the filter name. abs
([out])Return a new object with the absolute value of the data. add_asym_gaussian
(lpeak, flux, fwhm_right, …)Add an asymetric gaussian on spectrum in place. add_gaussian
(lpeak, flux, fwhm[, cont, …])Add a gaussian on spectrum in place. clone
([data_init, var_init])Return a shallow copy with the same header and coordinates. convolve
(other[, inplace])Convolve a Spectrum with a 1D array or another Spectrum, using the discrete convolution equation. copy
()Return a copy of the object. correlate
(other[, inplace])Crosscorrelate the spectrum with a other spectrum or an array. crop
()Reduce the size of the array to the smallest subarray that keeps all unmasked pixels. fftconvolve
(other[, inplace])Convolve a Spectrum with a 1D array or another Spectrum, using the Fourier convolution theorem. fftconvolve_gauss
(fwhm[, nsig, unit, inplace])Convolve the spectrum with a Gaussian using fft. fwhm
(l0[, cont, spline, unit])Return the fwhm of a peak. gauss_asymfit
(lmin, lmax[, lpeak, flux, …])Truncate the spectrum and fit it with an asymetric gaussian function. gauss_dfit
(lmin, lmax, wratio[, lpeak_1, …])Truncate the spectrum and fit it as a sum of two gaussian functions. gauss_fit
(lmin, lmax[, lpeak, flux, fwhm, …])Perform a Gaussian fit. get_data_hdu
([name, savemask])Return an ImageHDU corresponding to the DATA extension. get_end
([unit])Return the wavelength of the last pixel of the spectrum. get_range
([unit])Return the wavelength range (Lambda_min, Lambda_max) of the spectrum. get_start
([unit])Return the wavelength value of the first pixel of the spectrum. get_stat_hdu
([name, header])Return an ImageHDU corresponding to the STAT extension. get_step
([unit])Return the wavelength step size. get_wcs_header
()Return a FITS header containing coordinate descriptions. info
()Print information. integrate
([lmin, lmax, unit])Integrate the flux over a specified wavelength range. interp_mask
([spline])Interpolate masked pixels. line_gauss_fit
(**kwargs)mask_region
([lmin, lmax, inside, unit])Mask spectrum pixels inside or outside a wavelength range, [lmin,lmax]. mask_selection
(ksel)Mask selected pixels. mask_variance
(threshold)Mask pixels with a variance above a threshold value. mean
([lmin, lmax, weight, unit])Compute the mean flux over a specified wavelength range. median_filter
([kernel_size, spline, unit, …])Perform a median filter on the spectrum. new_from_obj
(obj[, data, var, copy])Create a new object from another one, copying its attributes. plot
([max, title, noise, snr, lmin, lmax, …])Plot the spectrum. poly_fit
(deg[, weight, maxiter, nsig, verbose])Perform polynomial fit on normalized spectrum and returns polynomial coefficients. poly_spec
(deg[, weight, maxiter, nsig, verbose])Return a spectrum containing a polynomial fit. poly_val
(z)Update in place the spectrum data from polynomial coefficients. rebin
(factor[, margin, inplace])Combine neighboring pixels to reduce the size of a spectrum by an integer factor. resample
(step[, start, shape, unit, …])Resample a spectrum to have a different wavelength interval. set_wcs
([wcs, wave])Set the world coordinates (spatial and/or spectral where pertinent). sqrt
([out])Return a new object with positive data squarerooted, and negative data masked. subspec
(lmin[, lmax, unit])Return the flux at a given wavelength, or the subspectrum of a specified wavelength range. sum
([lmin, lmax, weight, unit])Obtain the sum of the fluxes within a specified wavelength range. to_ds9
([ds9id, newframe, zscale, cmap])Send the data to ds9 (this will create a copy in memory) truncate
([lmin, lmax, unit])Truncate the wavelength range of a spectrum inplace. unmask
()Unmask the data (just invalid data (nan,inf) are masked). wavelet_filter
([levels, sigmaCutoff, …])Perform a wavelet filtering on the spectrum in 1 dimension. write
(filename[, savemask, checksum])Save the data to a FITS file. Attributes Documentation

data
¶ Return data as a
numpy.ma.MaskedArray
.The DataArray constructor postpones reading data from FITS files until they are first used. Read the data array here if not already read.
Changes can be made to individual elements of the data property. When simple numeric values or Numpy array elements are assigned to elements of the data property, the values of these elements are updated and become unmasked.
When masked Numpy values or maskedarray elements are assigned to elements of the data property, then these change both the values of the data property and the shared mask of the data and var properties.
Completely new arrays can also be assigned to the data property, provided that they have the same shape as before.

dtype
¶ The type of the data.

mask
¶ The shared masking array of the data and variance arrays.
This is a bool array which has the same shape as the data and variance arrays. Setting an element of this array to True, flags the corresponding pixels of the data and variance arrays, so that they don’t take part in subsequent calculations. Reverting this element to False, unmasks the pixel again.
This array can be modified either directly by assignments to elements of this property or by modifying the masks of the .data and .var arrays. An entirely new mask array can also be assigned to this property, provided that it has the same shape as the data array.

ndim
¶ The number of dimensions in the data and variance arrays : int

shape
¶ The lengths of each of the data axes.

var
¶ Return variance as a
numpy.ma.MaskedArray
.If variances have been provided for each data pixel, then this property can be used to record those variances. Normally this is a masked array which shares the mask of the data property. However if no variances have been provided, then this property is None.
Variances are typically provided along with the data values in the originating FITS file. Alternatively a variance array can be assigned to this property after the data have been read.
Note that any function that modifies the contents of the data array may need to update the array of variances accordingly. For example, after scaling pixel values by a constant factor c, the variances should be scaled by c**2.
When maskedarray values are assigned to elements of the var property, the mask of the new values is assigned to the shared mask of the data and variance properties.
Completely new arrays can also be assigned to the var property. When a masked array is assigned to the var property, its mask is combined with the existing shared mask, rather than replacing it.
Methods Documentation

LSF_convolve
(lsf, size, **kwargs)[source]¶ Convolve spectrum with LSF.
Parameters: lsf : python function
mpdaf.MUSE.LSF
object or function f describing the LSF.The first three parameters of the function f must be lbda (wavelength value in A), step (in A) and size (odd integer).
f returns an np.array with shape=2*(size/2)+1 and centered in lbda
Example: from mpdaf.MUSE import LSF
size : odd int
size of LSF in pixels.
kwargs : kwargs
it can be used to set function arguments.
Returns: out :
Spectrum

abmag_band
(lbda, dlbda)[source]¶ Compute AB magnitude corresponding to the wavelength band.
Parameters: lbda : float
Mean wavelength in Angstrom.
dlbda : float
Width of the wavelength band in Angstrom.
Returns: out : float, float
Magnitude value and its error

abmag_filter
(lbda, eff)[source]¶ Compute AB magnitude using array filter.
Parameters: lbda : float array
Wavelength values in Angstrom.
eff : float array
Efficiency values.
Returns: out : float, float
Magnitude value and its error

abmag_filter_name
(name)[source]¶ Compute AB magnitude using the filter name.
Parameters: name : string
‘U’, ‘B’, ‘V’, ‘Rc’, ‘Ic’, ‘z’, ‘RJohnson’, ‘F606W’, ‘F775W’, ‘F814W’, ‘F850LP’
Returns: out : float, float
Magnitude value and its error

abs
(out=None)¶ Return a new object with the absolute value of the data.
Parameters: out :
mpdaf.obj.DataArray
, optionalArray of the same shape as input, into which the output is placed. By default, a new array is created.

add_asym_gaussian
(lpeak, flux, fwhm_right, fwhm_left, cont=0, peak=False, unit=Unit("Angstrom"))[source]¶ Add an asymetric gaussian on spectrum in place.
Parameters: lpeak : float
Gaussian center.
flux : float
Integrated gaussian flux or gaussian peak value if peak is True.
fwhm_right : float
Gaussian fwhm on the right (red) side
fwhm_left : float
Gaussian fwhm on the right (red) side
cont : float
Continuum value.
peak : bool
If true, flux contains the gaussian peak value.
unit :
astropy.units.Unit
Type of the wavelength coordinates. If None, inputs are in pixels.

add_gaussian
(lpeak, flux, fwhm, cont=0, peak=False, unit=Unit("Angstrom"))[source]¶ Add a gaussian on spectrum in place.
Parameters: lpeak : float
Gaussian center.
flux : float
Integrated gaussian flux or gaussian peak value if peak is True.
fwhm : float
Gaussian fwhm.
cont : float
Continuum value.
peak : bool
If true, flux contains the gaussian peak value
unit :
astropy.units.Unit
Type of the wavelength coordinates. If None, inputs are in pixels.

clone
(data_init=None, var_init=None)¶ Return a shallow copy with the same header and coordinates.
Optionally fill the cloned array using values returned by provided functions.
Parameters: data_init : function
An optional function to use to create the data array (it takes the shape as parameter). For example
np.zeros
ornp.empty
can be used. It defaults to None, which results in the data attribute being None.var_init : function
An optional function to use to create the variance array, with the same specifics as data_init. This default to None, which results in the var attribute being assigned None.

convolve
(other, inplace=False)[source]¶ Convolve a Spectrum with a 1D array or another Spectrum, using the discrete convolution equation.
This function, which uses the discrete convolution equation, is usually slower than Image.fftconvolve(). However it can be faster when other.data.size is small, and it always uses much less memory, so it is sometimes the only practical choice.
Masked values in self.data and self.var are replaced with zeros before the convolution is performed, but are masked again after the convolution.
If self.var exists, the variances are propagated using the equation:
result.var = self.var (*) other**2where (*) indicates convolution. This equation can be derived by applying the usual rules of errorpropagation to the discrete convolution equation.
The speed of this function scales as O(Nd x No) where Nd=self.data.size and No=other.data.size.
Uses
scipy.signal.convolve
.Parameters: other : Spectrum or np.ndarray
The 1D array with which to convolve the spectrum in self.data. This can be an array of the same size as self, or it can be a smaller array, such as a small gaussian profile to use to smooth the spectrum.
When other.data contains a symmetric filtering function, such as a gaussian profile, the center of the function should be placed at the center of pixel:
(other.shape  1) // 2
If
other
is an MPDAF Spectrum object, note that only its data array is used. Masked values in this array are treated as zero. Any variances found in other.var are ignored.inplace : bool
If False (the default), return the results in a new Spectrum. If True, record the result in self and return that.
Returns: out :
Spectrum

copy
()¶ Return a copy of the object.

correlate
(other, inplace=False)[source]¶ Crosscorrelate the spectrum with a other spectrum or an array.
Uses
scipy.signal.correlate
. self and other must have the same size.Parameters: other : 1darray or Spectrum
Second spectrum or 1darray.
inplace : bool
If True, replace the input spectrum with the correlation.
Returns: out : Spectrum

crop
()¶ Reduce the size of the array to the smallest subarray that keeps all unmasked pixels.
This removes any margins around the array that only contain masked pixels. If all pixels are masked in the input cube, the data and variance arrays are deleted.
Returns: item : list of slices
The slices that were used to extract the subarray.

fftconvolve
(other, inplace=False)[source]¶ Convolve a Spectrum with a 1D array or another Spectrum, using the Fourier convolution theorem.
This function, which performs the convolution by multiplying the Fourier transforms of the two arrays, is usually much faster than Spectrum.convolve(), except when other.data.size is small. However it uses much more memory, so Spectrum.convolve() is sometimes a better choice.
Masked values in self.data and self.var are replaced with zeros before the convolution is performed, but they are masked again after the convolution.
If self.var exists, the variances are propagated using the equation:
result.var = self.var (*) other**2where (*) indicates convolution. This equation can be derived by applying the usual rules of errorpropagation to the discrete convolution equation.
The speed of this function scales as O(Nd x log(Nd)) where Nd=self.data.size. This function temporarily allocates a pair of arrays that have the sum of the shapes of self.shape and other.shape, rounded up to a power of two along each axis. This can involve a lot of memory being allocated. For this reason, when other.shape is small, Spectrum.convolve() may be more efficient than Spectrum.fftconvolve().
Uses
scipy.signal.fftconvolve
.Parameters: other : Spectrum or np.ndarray
The 1D array with which to convolve the spectrum in self.data. This can be an array of the same size as self.data, or it can be a smaller array, such as a small gaussian to use to smooth the spectrum.
When
other
contains a symmetric filtering function, such as a gaussian profile, the center of the function should be placed at the center of pixel:(other.shape  1) // 2
If other is an MPDAF Spectrum object, note that only its data array is used. Masked values in this array are treated as zero. Any variances found in other.var are ignored.
inplace : bool
If False (the default), return the results in a new Spectrum. If True, record the result in self and return that.
Returns: out :
Spectrum

fftconvolve_gauss
(fwhm, nsig=5, unit=Unit("Angstrom"), inplace=False)[source]¶ Convolve the spectrum with a Gaussian using fft.
Parameters: fwhm : float
Gaussian fwhm.
nsig : int
Number of standard deviations.
unit :
astropy.units.Unit
type of the wavelength coordinates
inplace : bool
If True, convolve the original spectrum inplace, and return that.
Returns: out : Spectrum

fwhm
(l0, cont=0, spline=False, unit=Unit("Angstrom"))[source]¶ Return the fwhm of a peak.
Parameters: l0 : float
Wavelength value corresponding to the peak position.
unit :
astropy.units.Unit
Type of the wavelength coordinates. If None, inputs are in pixels.
cont : int
The continuum [default 0].
spline : bool
Linear/spline interpolation to interpolate masked values.
Returns: out : float

gauss_asymfit
(lmin, lmax, lpeak=None, flux=None, fwhm=None, cont=None, peak=False, spline=False, weight=True, plot=False, plot_factor=10, unit=Unit("Angstrom"))[source]¶ Truncate the spectrum and fit it with an asymetric gaussian function.
Returns the two gaussian functions (right and left) as
mpdaf.obj.Gauss1D
objects.From Johan Richard and Vera Patricio, modified by Jeremy Blaizot.
Parameters: lmin : float or (float,float)
Minimum wavelength value or wavelength range used to initialize the gaussian left value.
lmax : float or (float,float)
Maximum wavelength or wavelength range used to initialize the gaussian right value.
lpeak : float
Input gaussian center. if None it is estimated with the wavelength corresponding to the maximum value in
[max(lmin), min(lmax)]
.flux : float
Integrated gaussian flux or gaussian peak value if peak is True.
fwhm : float
Input gaussian fwhm, if None it is estimated.
peak : bool
If true, flux contains the gaussian peak value .
cont : float
Continuum value, if None it is estimated by the line through points (max(lmin),mean(data[lmin])) and (min(lmax),mean(data[lmax])).
spline : bool
Linear/spline interpolation to interpolate masked values.
weight : bool
If weight is True, the weight is computed as the inverse of variance.
unit :
astropy.units.Unit
type of the wavelength coordinates. If None, inputs are in pixels.
plot : bool
If True, the resulted fit is plotted.
plot_factor : double
oversampling factor for the overplotted fit
Returns: out :
mpdaf.obj.Gauss1D
,mpdaf.obj.Gauss1D
Left and right Gaussian functions.

gauss_dfit
(lmin, lmax, wratio, lpeak_1=None, flux_1=None, fratio=1.0, fwhm=None, cont=None, peak=False, spline=False, weight=True, plot=False, plot_factor=10, unit=Unit("Angstrom"))[source]¶ Truncate the spectrum and fit it as a sum of two gaussian functions.
Returns the two gaussian functions as
mpdaf.obj.Gauss1D
objects.From Johan Richard and Vera Patricio.
Parameters: lmin : float or (float,float)
Minimum wavelength value or wavelength range used to initialize the gaussian left value.
lmax : float or (float,float)
Maximum wavelength or wavelength range used to initialize the gaussian right value.
wratio : float
Ratio between the two gaussian centers
lpeak_1 : float
Input gaussian center of the first gaussian. if None it is estimated with the wavelength corresponding to the maximum value in [max(lmin), min(lmax)]
flux_1 : float
Integrated gaussian flux or gaussian peak value if peak is True.
fratio : float
Ratio between the two integrated gaussian fluxes.
fwhm : float
Input gaussian fwhm, if None it is estimated.
peak : bool
If true, flux contains the gaussian peak value .
cont : float
Continuum value, if None it is estimated by the line through points (max(lmin),mean(data[lmin])) and (min(lmax),mean(data[lmax])).
spline : bool
Linear/spline interpolation to interpolate masked values.
weight : bool
If weight is True, the weight is computed as the inverse of variance.
plot : bool
If True, the resulted fit is plotted.
plot_factor : double
oversampling factor for the overplotted fit
unit :
astropy.units.Unit
Type of the wavelength coordinates. If None, inputs are in pixels.
Returns:

gauss_fit
(lmin, lmax, lpeak=None, flux=None, fwhm=None, cont=None, peak=False, spline=False, weight=True, plot=False, plot_factor=10, unit=Unit("Angstrom"), fix_lpeak=False)[source]¶ Perform a Gaussian fit.
Uses
scipy.optimize.leastsq
to minimize the sum of squares.Parameters: lmin : float or (float,float)
Minimum wavelength value or wavelength range used to initialize the gaussian left value (in angstrom)
lmax : float or (float,float)
Maximum wavelength or wavelength range used to initialize the gaussian right value (in angstrom)
lpeak : float
Input gaussian center (in angstrom), if None it is estimated with the wavelength corresponding to the maximum value in [max(lmin), min(lmax)]
unit :
astropy.units.Unit
Type of the wavelength coordinates. If None, inputs are in pixels.
flux : float
Integrated gaussian flux or gaussian peak value if peak is True.
fwhm : float
Input gaussian fwhm (in angstrom), if None it is estimated.
peak : bool
If true, flux contains the gaussian peak value .
cont : float
Continuum value, if None it is estimated by the line through points (max(lmin),mean(data[lmin])) and (min(lmax),mean(data[lmax])).
spline : bool
Linear/spline interpolation to interpolate masked values.
weight : bool
If weight is True, the weight is computed as the inverse of variance.
plot : bool
If True, the Gaussian is plotted.
plot_factor : double
oversampling factor for the overplotted fit
Returns: out :
mpdaf.obj.Gauss1D

get_data_hdu
(name='DATA', savemask='dq')¶ Return an ImageHDU corresponding to the DATA extension.
Parameters: name : str
Extension name, DATA by default.
savemask : str
If ‘dq’, the mask array is saved in a DQ extension. If ‘nan’, masked data are replaced by nan in a DATA extension. If ‘none’, masked array is not saved.
Returns: out :
astropy.io.fits.ImageHDU

get_end
(unit=None)[source]¶ Return the wavelength of the last pixel of the spectrum.
Parameters: unit :
astropy.units.Unit
The units of the returned wavelength.
Returns: out : float
The wavelength of the final pixel of the spectrum.

get_range
(unit=None)[source]¶ Return the wavelength range (Lambda_min, Lambda_max) of the spectrum.
Parameters: unit :
astropy.units.Unit
The units of the returned wavelengths.
Returns: out : float array
The minimum and maximum wavelengths.

get_start
(unit=None)[source]¶ Return the wavelength value of the first pixel of the spectrum.
Parameters: unit :
astropy.units.Unit
The units of the returned wavelength.
Returns: out : float
The wavelength of the first pixel of the spectrum.

get_stat_hdu
(name='STAT', header=None)¶ Return an ImageHDU corresponding to the STAT extension.
Parameters: name : str
Extension name, STAT by default.
Returns: out :
astropy.io.fits.ImageHDU

get_step
(unit=None)[source]¶ Return the wavelength step size.
Parameters: unit :
astropy.units.Unit
The units of the returned stepsize.
Returns: out : float
The width of a spectrum pixel.

get_wcs_header
()¶ Return a FITS header containing coordinate descriptions.

info
()¶ Print information.

integrate
(lmin=None, lmax=None, unit=Unit("Angstrom"))[source]¶ Integrate the flux over a specified wavelength range.
The units of the integrated flux depend on the flux units of the spectrum and the wavelength units, as follows:
If the flux units of the spectrum, self.unit, are something like Q per angstrom, Q per nm, or Q per um, then the integrated flux will have the units of Q. For example, if the fluxes have units of 1e20 erg/cm2/Angstrom/s, then the units of the integration will be 1e20 erg/cm2/s.
Alternatively, if unit is not None, then the unit of the returned number will be the product of the units in self.unit and unit. For example, if the flux units are counts/s, and unit=u.angstrom, then the integrated flux will have units counts*Angstrom/s.
Finally, if unit is None, then the units of the returned number will be the product of self.unit and the units of the wavelength axis of the spectrum (ie. self.wave.unit).
The result of the integration is returned as an astropy Quantity, which holds the integrated value and its physical units. The units of the returned number can be determined from the .unit attribute of the return value. Alternatively the returned value can be converted to another unit, using the to() method of astropy quantities.
Parameters: lmin : float
The minimum wavelength of the range to be integrated, or None (the default), to select the minimum wavelength of the first pixel of the spectrum. If this is below the minimum wavelength of the spectrum, the integration behaves as though the flux in the first pixel extended down to that wavelength.
If the unit argument is None, lmin is a pixel index, and the wavelength of the center of this pixel is used as the lower wavelength of the integration.
lmax : float
The maximum wavelength of the range to be integrated, or None (the default), to select the maximum wavelength of the last pixel of the spectrum. If this is above the maximum wavelength of the spectrum, the integration behaves as though the flux in the last pixel extended up to that wavelength.
If the unit argument is None, lmax is a pixel index, and the wavelength of the center of this pixel is used as the upper wavelength of the integration.
unit :
astropy.units.Unit
The wavelength units of lmin and lmax, or None to indicate that lmin and lmax are pixel indexes.
Returns: out :
astropy.units.Quantity
,astropy.units.Quantity
The result of the integration and its error, expressed as a floating point number with accompanying units. The integrated value and its physical units can be extracted using the .value and .unit attributes of the returned quantity. The value can also be converted to different units, using the .to() method of the returned objected.

interp_mask
(spline=False)[source]¶ Interpolate masked pixels.
Parameters: spline : bool
False: linear interpolation (use
scipy.interpolate.interp1d
), True: spline interpolation (usescipy.interpolate.splrep
andscipy.interpolate.splev
).

mask_region
(lmin=None, lmax=None, inside=True, unit=Unit("Angstrom"))[source]¶ Mask spectrum pixels inside or outside a wavelength range, [lmin,lmax].
Parameters: lmin : float
The minimum wavelength of the range, or None to choose the wavelength of the first pixel in the spectrum.
lmax : float
The maximum wavelength of the range, or None to choose the wavelength of the last pixel in the spectrum.
unit :
astropy.units.Unit
The wavelength units of lmin and lmax. If None, lmin and lmax are assumed to be pixel indexes.
inside : bool
If True, pixels inside the range [lmin,lmax] are masked. If False, pixels outside the range [lmin,lmax] are masked.

mask_selection
(ksel)¶ Mask selected pixels.
Parameters: ksel : output of np.where
Elements depending on a condition

mask_variance
(threshold)¶ Mask pixels with a variance above a threshold value.
Parameters: threshold : float
Threshold value.

mean
(lmin=None, lmax=None, weight=True, unit=Unit("Angstrom"))[source]¶ Compute the mean flux over a specified wavelength range.
Parameters: lmin : float
The minimum wavelength of the range, or None to choose the wavelength of the first pixel in the spectrum.
lmax : float
The maximum wavelength of the range, or None to choose the wavelength of the last pixel in the spectrum.
unit :
astropy.units.Unit
The wavelength units of lmin and lmax. If None, lmin and lmax are assumed to be pixel indexes.
weight : bool
If weight is True, compute the weighted mean, inversely weighting each pixel by its variance.
Returns: out : (float, float)
The mean flux and its error.

median_filter
(kernel_size=1.0, spline=False, unit=Unit("Angstrom"), inplace=False)[source]¶ Perform a median filter on the spectrum.
Uses
scipy.signal.medfilt
.Parameters: kernel_size : float
Size of the median filter window.
unit :
astropy.units.Unit
unit ot the kernel size
inplace : bool
If False, return a filtered copy of the spectrum (the default). If True, filter the original spectrum inplace, and return that.
Returns: out : Spectrum

classmethod
new_from_obj
(obj, data=None, var=None, copy=False)¶ Create a new object from another one, copying its attributes.
Parameters: obj :
mpdaf.obj.DataArray
The object to use as the template for the new object. This should be an object based on DataArray, such as an Image, Cube or Spectrum.
data : ndarraylike
An optional data array, or None to indicate that
obj.data
should be used. The default is None.var : ndarraylike
An optional variance array, or None to indicate that
obj.var
should be used, or False to indicate that the new object should not have any variances. The default is None.copy : bool
Copy the data and variance arrays if True (default False).

plot
(max=None, title=None, noise=False, snr=False, lmin=None, lmax=None, ax=None, stretch='linear', unit=Unit("Angstrom"), noise_kwargs=None, **kwargs)[source]¶ Plot the spectrum.
By default, the matplotlib drawstyle option is set to ‘stepsmid’. The reason for this is that in MPDAF integer pixel indexes correspond to the centers of their pixels, and the floating point pixel indexes of a pixel extend from half a pixel below the integer central position to half a pixel above it.
Parameters: max : float
If max is not None (the default), it should be a floating point value. The plotted data will be renormalized such that the peak in the plot has this value.
title : string
The title to give the figure (None by default).
noise : bool
If noise is True, colored extensions above and below the plotted points indicate the squareroot of the variances of each pixel (if any).
snr : bool
If snr is True, data/sqrt(var) is plotted.
lmin : float
The minimum wavelength to be plotted, or None (the default) to start the plot from the minimum wavelength in the spectrum.
lmax : float
The maximum wavelength to be plotted, or None (the default) to start the plot from the maximum wavelength in the spectrum.
ax : matplotlib.Axes
The Axes instance in which the spectrum is drawn, or None (the default), to request that an Axes object be created internally.
unit :
astropy.units.Unit
The wavelength units of the lmin and lmax arguments, or None to indicate that lmin and lmax are floating point pixel indexes.
noise_kwargs : dict
Properties for the noise plot (if
noise=True
). Default tocolor='0.75', facecolor='0.75', alpha=0.5
.kwargs : dict
kwargs can be used to set properties of the plot such as: line label (for auto legends), linewidth, anitialising, marker face color, etc.

poly_fit
(deg, weight=True, maxiter=0, nsig=(3.0, 3.0), verbose=False)[source]¶ Perform polynomial fit on normalized spectrum and returns polynomial coefficients.
Parameters: deg : int
Polynomial degree.
weight : bool
If weight is True, the weight is computed as the inverse of variance.
maxiter : int
Maximum allowed iterations (0)
nsig : (float,float)
The low and high rejection factor in std units (3.0,3.0)
Returns: out : ndarray, shape.
Polynomial coefficients ordered from low to high.

poly_spec
(deg, weight=True, maxiter=0, nsig=(3.0, 3.0), verbose=False)[source]¶ Return a spectrum containing a polynomial fit.
Parameters: deg : int
Polynomial degree.
weight : bool
If weight is True, the weight is computed as the inverse of variance.
maxiter : int
Maximum allowed iterations (0)
nsig : (float,float)
The low and high rejection factor in std units (3.0,3.0)
Returns: out : Spectrum

poly_val
(z)[source]¶ Update in place the spectrum data from polynomial coefficients.
Uses
numpy.poly1d
.Parameters: z : array
The polynomial coefficients, in increasing powers:
data = z0 + z1(lbdamin(lbda))/(max(lbda)min(lbda)) + … + zn ((lbdamin(lbda))/(max(lbda)min(lbda)))**n

rebin
(factor, margin='center', inplace=False)[source]¶ Combine neighboring pixels to reduce the size of a spectrum by an integer factor.
Each output pixel is the mean of n pixels, where n is the specified reduction factor.
Parameters: factor : int
The integer reduction factor by which the spectrum should be shrunk.
margin : string in ‘center’’right’’left’’origin’
When the dimension of the input spectrum is not an integer multiple of the reduction factor, the spectrum is truncated to remove just enough pixels that its length is a multiple of the reduction factor. This subspectrum is then rebinned in place of the original spectrum. The margin parameter determines which pixels of the input spectrum are truncated, and which remain.
 The options are:
 ‘origin’ or ‘center’:
The start of the output spectrum is coincident with the start of the input spectrum.
 ‘center’:
The center of the output spectrum is aligned with the center of the input spectrum, within one pixel.
 ‘right’:
The end of the output spectrum is coincident with the end of the input spectrum.
inplace : bool
If False, return a rebinned copy of the spectrum (the default). If True, rebin the original spectrum inplace, and return that.
Returns: out : Spectrum

resample
(step, start=None, shape=None, unit=Unit("Angstrom"), inplace=False, atten=40.0, cutoff=0.25)[source]¶ Resample a spectrum to have a different wavelength interval.
Parameters: step : float
The new pixel size along the wavelength axis of the spectrum.
start : float
The wavelength at the center of the first pixel of the resampled spectrum. If None (the default) the center of the first pixel has the same wavelength before and after resampling.
unit :
astropy.units.Unit
The wavelength units of the step and start arguments. The default is u.angstrom.
shape : int
The dimension of the array of the new spectrum (ie. the number of spectral pixels). If this is not specified, the shape is selected to encompass the wavelength range from the chosen start wavelength to the ending wavelength of the input spectrum.
inplace : bool
If False, return a resampled copy of the spectrum (the default). If True, resample the original spectrum inplace, and return that.
atten : float
The minimum attenuation (dB), of the antialiasing decimation filter at the Nyquist folding frequency of the new pixel size. Larger attenuations suppress aliasing better at the expense of worsened resolution. The default attenuation is 40.0 dB. To disable antialiasing, specify atten=0.0.
cutoff : float
Mask each output pixel of which at least this fraction of the pixel was interpolated from masked input pixels.
Returns: out : Spectrum

set_wcs
(wcs=None, wave=None)¶ Set the world coordinates (spatial and/or spectral where pertinent).
Parameters: wcs :
mpdaf.obj.WCS
Spatial world coordinates. This argument is ignored when self is a Spectrum.
wave :
mpdaf.obj.WaveCoord
Spectral wavelength coordinates. This argument is ignored when self is an Image.

sqrt
(out=None)¶ Return a new object with positive data squarerooted, and negative data masked.
Parameters: out :
mpdaf.obj.DataArray
, optionalArray of the same shape as input, into which the output is placed. By default, a new array is created.

subspec
(lmin, lmax=None, unit=Unit("Angstrom"))[source]¶ Return the flux at a given wavelength, or the subspectrum of a specified wavelength range.
A single flux value is returned if the lmax argument is None (the default), or if the wavelengths assigned to the lmin and lmax arguments are both within the same pixel. The value that is returned is the value of the pixel whose wavelength is closest to the wavelength specified by the lmin argument.
Parameters: lmin : float
The minimum wavelength of a wavelength range, or the wavelength of a single pixel if lmax is None.
lmax : float or None
The maximum wavelength of the wavelength range.
unit :
astropy.units.Unit
The wavelength units of the lmin and lmax arguments. The default is angstroms. If unit is None, then lmin and lmax are interpreted as array indexes within the spectrum.
Returns: out : float or
Spectrum

sum
(lmin=None, lmax=None, weight=True, unit=Unit("Angstrom"))[source]¶ Obtain the sum of the fluxes within a specified wavelength range.
Parameters: lmin : float
The minimum wavelength of the range, or None to choose the wavelength of the first pixel in the spectrum.
lmax : float
The maximum wavelength of the range, or None to choose the wavelength of the last pixel in the spectrum.
unit :
astropy.units.Unit
The wavelength units of lmin and lmax. If None, lmin and lmax are assumed to be pixel indexes.
weight : bool
If weight is True, compute the weighted sum, inversely weighting each pixel by its variance.
Returns: out : float, float
The total flux and its error.

to_ds9
(ds9id=None, newframe=False, zscale=False, cmap='grey')¶ Send the data to ds9 (this will create a copy in memory)
Parameters: ds9id: None or str
The DS9 session ID. If ‘None’, a new one will be created. To find your ds9 session ID, open the ds9 menu option File:XPA:Information and look for the XPA_METHOD string, e.g.
XPA_METHOD: 86ab2314:60063
. You would then calll this function ascube.to_ds9('86ab2314:60063')
newframe: bool
Send the cube to a new frame or to the current frame?

truncate
(lmin=None, lmax=None, unit=Unit("Angstrom"))[source]¶ Truncate the wavelength range of a spectrum inplace.
Parameters: lmin : float
The minimum wavelength of a wavelength range, or the wavelength of a single pixel if lmax is None.
lmax : float or None
The maximum wavelength of the wavelength range.
unit :
astropy.units.Unit
The wavelength units of the lmin and lmax arguments. The default is angstroms. If unit is None, then lmin and lmax are interpreted as array indexes within the spectrum.

unmask
()¶ Unmask the data (just invalid data (nan,inf) are masked).

wavelet_filter
(levels=9, sigmaCutoff=5.0, epsilon=0.05, inplace=False)[source]¶ Perform a wavelet filtering on the spectrum in 1 dimension.
Code contributed by Markus Rexroth (EPFL, 2016), and used in https://arxiv.org/abs/1703.09239 (with funding from ERC Advanced Grant LIDA, Swiss National Science Foundation, ERC Starting Grant 336736CALENDS).
Parameters: levels : int
Highest scale level.
sigmaCutoff : float
Cleaning threshold. By default 5 for a 5 sigma cleaning in wavelet space.
epsilon : float in ]0,1[
Residual criterion used to perform the cleaning
inplace : bool
If False, return a filtered copy of the spectrum (the default). If True, filter the original spectrum inplace, and return that.
Returns: out : Spectrum

write
(filename, savemask='dq', checksum=False)¶ Save the data to a FITS file.
Overwrite the file if it exists.
Parameters: filename : str
The FITS filename.
savemask : str
If ‘dq’, the mask array is saved in a
DQ
extension If ‘nan’, masked data are replaced by nan in theDATA
extension If ‘none’, masked array is not savedchecksum : bool
If
True
, adds bothDATASUM
andCHECKSUM
cards to the headers of all HDU’s written to the file.
