IQCalc

class ginga.util.iqcalc_astropy.IQCalc(*args, **kwargs)[source]

Bases: IQCalc

This is ginga.util.iqcalc.IQCalc that uses astropy.

This subclass has an extra self.fitter attribute for astropy fitting.

Methods Summary

`calc_fwhm`(arr1d[, medv, method_name])	Calculate FWHM for the given input array.
`calc_fwhm_gaussian`(arr1d[, medv])	FWHM calculation on a 1D array by using least square fitting of a Gaussian function on the data.
`calc_fwhm_lorentz`(arr1d[, medv])	FWHM calculation on a 1D array by using least square fitting of a Lorentz function on the data.
`calc_fwhm_moffat`(arr1d[, medv])	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.
`find_bright_peaks`(data[, threshold, sigma, ...])	Find bright peak candidates in in the given data.
`gaussian`(x, p)	Evaluate Gaussian function in 1D.
`lorentz`(x, p)	Evaluate Lorentz function in 1D.
`moffat`(x, p)	Evaluate Moffat function in 1D.

Methods Documentation

calc_fwhm(arr1d, medv=None, method_name='gaussian')[source]

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’, ‘lorentz’}: Function to use for fitting.

Returns:

resBunch: Fitting results.

Raises:

NotImplementedError: Given function is not supported.

calc_fwhm_gaussian(arr1d, medv=None, **kwargs)[source]

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.
kwargsdict: Not used; for backward-compatible API call only.

Returns:

resBunch: Fitting results.

Raises:

IQCalcError: Fitting failed.

calc_fwhm_lorentz(arr1d, medv=None, **kwargs)[source]

FWHM calculation on a 1D array by using least square fitting of a Lorentz 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.
kwargsdict: Not used; for backward-compatible API call only.

Returns:

resBunch: Fitting results.

Raises:

IQCalcError: Fitting failed.

calc_fwhm_moffat(arr1d, medv=None, **kwargs)[source]

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.
kwargsdict: Not used; for backward-compatible API call only.

Returns:

resBunch: Fitting results.

Raises:

IQCalcError: Fitting failed.

centroid(data, xc, yc, radius)[source]

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.

find_bright_peaks(data, threshold=None, sigma=5, radius=5)[source]

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.

gaussian(x, p)[source]

Evaluate Gaussian function in 1D.

Parameters:

xarray-like: X values.
ptuple of float: Parameters for Gaussian, i.e., (mean, stddev, amplitude).

Returns:

yarray-like: Y values.

lorentz(x, p)[source]

Evaluate Lorentz function in 1D.

Parameters:

xarray-like: X values.
ptuple of float: Parameters for Lorentz, i.e., (x_0, fwhm, amplitude).

Returns:

yarray-like: Y values.

moffat(x, p)[source]

Evaluate Moffat function in 1D.

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.