IQCalc

class ginga.util.iqcalc.IQCalc(logger=None)

Bases: object

Class to handle model fitting and FWHM calculations.

Parameters:

loggerobj or None

Python logger. If not given, one will be created.

Attributes:

lockthreading.RLock

For mutex around scipy.optimize, which seems to be non-threadsafe.

skylevel_magnification, skylevel_offsetfloat

For adjustments to sky background level.

Methods Summary

brightness(x, y, radius, medv, data)	Return the brightness value found in a region defined by input location and radius.
calc_fwhm(arr1d[, medv, method_name])	Calculate FWHM for the given input array.
calc_fwhm_gaussian(arr1d[, medv, gauss_fn])	FWHM calculation on a 1D array by using least square fitting of a Gaussian function on the data.
calc_fwhm_moffat(arr1d[, medv, moffat_fn])	FWHM calculation on a 1D array by using least square fitting of a Moffat function on the data.
centroid(data, xc, yc, radius)	Calculate centroid from center of mass.
cut_cross(x, y, radius, data)	Cut data vertically and horizontally at the given position with the given radius.
cut_region(x, y, radius, data)	Return a cut region.
encircled_energy(data)	Return a function of encircled energy across pixel indices.
ensquared_energy(data)	Return a function of ensquared energy across pixel indices.
evaluate_peaks(peaks, data[, fwhm_radius, ...])	Evaluate photometry for given peaks in data array.
find_bright_peaks(data[, threshold, sigma, ...])	Find bright peak candidates in in the given data.
fwhm_data(x, y, data[, radius, method_name])	Equivalent to get_fwhm().
gaussian(x, p)	Evaluate Gaussian function in 1D.
get_fwhm(x, y, radius, data[, medv, method_name])	Get the FWHM values of the object at the given coordinates and radius.
get_threshold(data[, sigma])	Calculate threshold for find_bright_peaks().
moffat(x, p)	Evaluate Moffat function in 1D.
objlist_select(objlist, width, height[, ...])	Filter output from evaluate_peaks().
pick_field(data[, peak_radius, fwhm_radius, ...])	Pick the first good object within the given field.
qualsize(image[, x1, y1, x2, y2, radius, ...])	Run pick_field() on the given image.
starsize(fwhm_x, deg_pix_x, fwhm_y, deg_pix_y)	Calculate average FWHM in arcseconds.

Methods Documentation

brightness(x, y, radius, medv, data)

Return the brightness value found in a region defined by input location and radius. Region is cut using cut_region().

Parameters:

x, yint

Indices of central pixel.

radiusint

Half-width in both X and Y directions.

medvfloat

Background to subtract off.

dataarray-like

Data array.

Returns:

resfloat

Brightness.

calc_fwhm(arr1d, medv=None, method_name='gaussian')

Calculate FWHM for the given input array.

Parameters:

arr1darray-like

1D array cut in either X or Y direction on the object.

medvfloat or None

Median of the data. If not given, it is calculated from arr1d.

method_name{‘gaussian’, ‘moffat’}

Function to use for fitting.

Returns:

resBunch

Fitting results.

calc_fwhm_gaussian(arr1d, medv=None, gauss_fn=None)

FWHM calculation on a 1D array by using least square fitting of a Gaussian function on the data.

Parameters:

arr1darray-like

1D array cut in either X or Y direction on the object.

medvfloat or None

Median of the data. If not given, it is calculated from arr1d.

gauss_fnfunc or None

Gaussian function for fitting. If not given, gaussian() is used.

Returns:

resBunch

Fitting results.

Raises:

IQCalcError

Fitting failed.

calc_fwhm_moffat(arr1d, medv=None, moffat_fn=None)

FWHM calculation on a 1D array by using least square fitting of a Moffat function on the data.

Parameters:

arr1darray-like

1D array cut in either X or Y direction on the object.

medvfloat or None

Median of the data. If not given, it is calculated from arr1d.

moffat_fnfunc or None

Moffat function for fitting. If not given, moffat() is used.

Returns:

resBunch

Fitting results.

Raises:

IQCalcError

Fitting failed.

centroid(data, xc, yc, radius)

Calculate centroid from center of mass.

Parameters:

dataarray-like

Data array.

xc, ycint

X and Y indices of the approximate center.

radiusfloat

Half-width of the region to consider around the given center.

Returns:

x, yfloat

Centroid indices.

Raises:

IQCalcError

Missing dependency.

cut_cross(x, y, radius, data)

Cut data vertically and horizontally at the given position with the given radius.

Parameters:

x, yint

Indices where vertical and horizontal cuts meet.

radiusfloat

Radius of both cuts.

dataarray-like

Data array to cut from.

Returns:

x0array-like

Starting pixel of horizontal cut (in X).

y0array-like

Starting pixel of vertical cut (in Y).

xarrarray-like

Horizontal cut (in X).

yarrarray-like

Vertical cut (in Y).

cut_region(x, y, radius, data)

Return a cut region.

Parameters:

x, yint

Indices of central pixel.

radiusint

Half-width in both X and Y directions.

dataarray-like

Data array to cut from.

Returns:

x0, y0int

Origin of the region.

arrarray-like

Cut region (a view, not copy).

encircled_energy(data)

Return a function of encircled energy across pixel indices.

Ideally, data is already a masked array and is assumed to be centered.

ensquared_energy(data)

Return a function of ensquared energy across pixel indices.

Ideally, data is already a masked array and is assumed to be centered.

evaluate_peaks(peaks, data, fwhm_radius=15, fwhm_method='gaussian', ee_total_radius=10, cb_fn=None, ev_intr=None)

Evaluate photometry for given peaks in data array.

Parameters:

peakslist of tuple

List of (x, y) tuples containing indices of peaks.

dataarray-like

Data array that goes with the given peaks.

fwhm_radius, fwhm_method

See get_fwhm().

ee_total_radiusfloat

Radius, in pixels, where encircled and ensquared energy fractions are defined as 1.

cb_fnfunc or None

If applicable, provide a callback function that takes a ginga.misc.Bunch.Bunch containing the result for each peak. It should not return anything.

ev_intrthreading.Event or None

For threading, if applicable.

.. note:: unused parameter `bright_radius` was removed in

release 4.0

Returns:

objlistlist of ginga.misc.Bunch.Bunch

A list of successful results for the given peaks. Each result contains the following keys:

• objx, objy: Fitted centroid from get_fwhm().

• pos: A measure of distance from the center of the image.

• oid_x, oid_y: Center-of-mass centroid from centroid().

• fwhm_x, fwhm_y: Fitted FWHM from get_fwhm().

• fwhm: Overall measure of fwhm as a single value.

• fwhm_radius: Input FWHM radius.

• brightness: Average peak value based on get_fwhm() fits.

• elipse: A measure of ellipticity.

• x, y: Input indices of the peak.

• skylevel: Sky level estimated from median of data array and skylevel_magnification and skylevel_offset attributes.

• background: Median of the input array.

• ensquared_energy_fn: Function of ensquared energy for different pixel radii.

• encircled_energy_fn: Function of encircled energy for different pixel radii.

find_bright_peaks(data, threshold=None, sigma=5, radius=5)

Find bright peak candidates in in the given data.

Parameters:

dataarray-like

Input data to find peaks from.

thresholdfloat or None

Detection threshold. Below this value, an object is not considered a candidate. If not given, a default is calculated using get_threshold() with the given sigma.

sigmafloat

Sigma for the threshold.

radiusfloat

Pixel radius for determining local maxima. If the desired objects are larger in size, specify a larger radius.

Returns:

peakslist of tuple

A list of candidate object coordinate tuples (x, y) in data.

fwhm_data(x, y, data, radius=15, method_name='gaussian')

Equivalent to get_fwhm().

gaussian(x, p)

Evaluate Gaussian function in 1D. See calc_fwhm().

Parameters:

xarray-like

X values.

ptuple of float

Parameters for Gaussian, i.e., (mean, stddev, amplitude).

Returns:

yarray-like

Y values.

get_fwhm(x, y, radius, data, medv=None, method_name='gaussian')

Get the FWHM values of the object at the given coordinates and radius.

Parameters:

x, yint

Indices of the object location in data array.

radiusfloat

Radius of the region encompassing the object.

dataarray-like

Data array.

medv, method_name

See calc_fwhm().

Returns:

fwhm_x, fwhm_yfloat

FWHM in X and Y, respectively.

ctr_x, ctr_yfloat

Center in X and Y, respectively.

x_res, y_resdict

Fit results from calc_fwhm() in X and Y, respectively.

get_threshold(data, sigma=5.0)

Calculate threshold for find_bright_peaks().

Parameters:

dataarray-like

Data array.

sigmafloat

Sigma for the threshold.

Returns:

thresholdfloat

Threshold based on good data, its median, and the given sigma.

moffat(x, p)

Evaluate Moffat function in 1D. See calc_fwhm().

Parameters:

xarray-like

X values.

ptuple of float

Parameters for Moffat, i.e., (x_0, gamma, alpha, amplitude), where x_0 a.k.a. mean and gamma core width.

Returns:

yarray-like

Y values.

objlist_select(objlist, width, height, minfwhm=2.0, maxfwhm=150.0, minelipse=0.5, edgew=0.01)

Filter output from evaluate_peaks().

Parameters:

objlistlist of ginga.misc.Bunch.Bunch

Output from evaluate_peaks().

width, heightint

Dimension of data array from which objlist was derived.

minfwhm, maxfwhmfloat

Limits for desired FWHM, where (minfwhm, maxfwhm).

minelipsefloat

Minimum value of desired ellipticity (not inclusive).

edgewfloat

Factor between 0 and 1 that determines if a location is too close to the edge or not.

Returns:

resultslist of ginga.misc.Bunch.Bunch

Elements of objlist that contain desired FWHM, ellipticity, and not too close to the edge.

pick_field(data, peak_radius=5, fwhm_radius=15, threshold=None, minfwhm=2.0, maxfwhm=50.0, minelipse=0.5, edgew=0.01, ee_total_radius=10)

Pick the first good object within the given field.

Parameters:

dataarray-like

Data array of the field.

peak_radius, threshold

See find_bright_peaks().

fwhm_radius, ee_total_radius

See evaluate_peaks().

minfwhm, maxfwhm, minelipse, edgew

See objlist_select().

.. note:: unused parameter `bright_radius` was removed in

release 4.0

Returns:

resultginga.misc.Bunch.Bunch

This is a single element of objlist as described in evaluate_peaks().

Raises:

IQCalcError

No object matches selection criteria.

qualsize(image, x1=None, y1=None, x2=None, y2=None, radius=5, fwhm_radius=15, threshold=None, minfwhm=2.0, maxfwhm=50.0, minelipse=0.5, edgew=0.01, ee_total_radius=10)

Run pick_field() on the given image.

Parameters:

imageginga.AstroImage.AstroImage

Image to process.

x1, y1, x2, y2int

See ginga.BaseImage.BaseImage.cutout_data().

radius, threshold

See find_bright_peaks().

fwhm_radius, ee_total_radius

See evaluate_peaks().

minfwhm, maxfwhm, minelipse, edgew

See objlist_select().

.. note:: unused parameter `bright_radius` was removed in

release 4.0

Returns:

qsginga.misc.Bunch.Bunch

This is a single element of objlist as described in evaluate_peaks().

starsize(fwhm_x, deg_pix_x, fwhm_y, deg_pix_y)

Calculate average FWHM in arcseconds.

Parameters:

fwhm_xfloat

FWHM in X (pixels).

deg_pix_xfloat

Plate scale from CDELT1 in degrees per pixel.

fwhm_yfloat

FWHM in Y (pixels).

deg_pix_yfloat

Plate scale from CDELT2 in degrees per pixel.

Returns:

fwhmfloat

Average FWHM in arcseconds.