tracespec

sofia_redux.spectroscopy.tracespec.tracespec(rectimg, positions, orders=None, fwhm=1.0, step=3, sumap=3, winthresh=5, fitorder=2, fitthresh=3, polyfit_kwargs=None, info=None, fast=False, **kwargs)

Trace spectral continua in a spatially/spectrally rectified image.

Determines trace coefficients for the center of the aperture via fits to the continuum. Within an order, sumap columns are added together to increase the total signal. A Gaussian is then fitted around the guess position. If within winthresh pixels of a guess, the position is stored. The resulting positions are then fitted with a polynomial of degree fitorder.

The rectimg value should come from sofia_redux.spectroscopy.rectify.

Parameters:

rectimgdict

Rectified image data, as returned by sofia_redux.spectroscopy.rectify with integer keys. Each order value is a dictionary with keys:

"image"

Rectified image array. (ns, nw) array, required.

"wave"

Wave coordinates along image axis=1. (nw,) array, required.

"spatial"

Spatial coordinates along image axis=0. (ns,) array, required.

positionsdict

List of aperture positions by order, given as arcsec up the slit. Keys are integers, values are lists of floats.

ordersarray_like of int, optional

Order numbers to process. If not provided, all orders in positions will be processed.

stepint, optional

Pixel step size in the dispersion direction used to determine the trace.

sumapint, optional

Number of columns to add together. Must be odd and less than 2 * step.

winthreshfloat, optional

The threshold over which an identified peak is ignored. If the difference between the guess position is larger than winthresh, the fitted position is ignored.

fitorderint, optional

Polynomial fit degree used to determine the trace coefficients.

fitthreshfloat, optional

Sigma threshold used to identify outliers.

polyfit_kwargsdict, optional

Optional keyword arguments for the polynomial fit to the trace (spatial location of peak vs wavecal). These will be passed to sofia_redux.toolkit.fitting.polyfit.

infodict, optional

If supplied will be updated as follows:

orderint

xnumpy.ndarray

(n_apertures, n_steps) array of fitted trace pixel coordinates in x.

ynumpy.ndarray

(n_apertures, n_steps) array of fitted trace pixel coordinates in y.

masknumpy.ndarray

(n_apertures, n_steps) array of bool where True indicates that the peak fit on that step of columns was included in the final calculation of trace coefficients.

trace_modelnumpy.ndarray

(n_apertures) array containing instances of astropy.modeling.polynomial.Polynomial1D models if aperture traces.

fitnumpy.ndarray

(n_apertures, n_steps, n_parameters) array of peak fit coefficients calculated by mc.fitpeaks1d at each step.

spatialnumpy.ndarray

(n_apertures, n_steps) array containing the spatial coordinates at each step.

wavenumpy.ndarray

(n_apertures, n_steps) array containing the wave coordinates at each step.

peak_modelastropy.modeling.Fittable1DModel

model used to fit peaks via fitpeaks1d

fastbool, optional

If set, use scipy.optimize.curve_fit to calculate spatial peak coefficients instead of the more flexible optimization in sofia_redux.toolkit.fitting.fitpeaks1d. If NaNs may be present, fast must be False.

kwargsdict, optional

Keyword arguments for sofia_redux.toolkit.fitting.fitpeaks1d. By default this will fit a single 1-D Gaussian peak and a constant background offset to each (median combined +/- sumap/2 @ step interval) column.

Returns:

trace_coefficientsdict

Array of polynomial fit coefficients by aperture and order. Coefficients are of the form:

spatial_position = c[0] + c[1].w + c[2].w^2 + … + c[n].w^n

where n ranges from 0 to fit_order and w is the wave value and c are the trace coefficients for a given order and aperture.

Keys and values are:

orderint

(n_apertures, n_coeff) array