Skip to content
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
14 changes: 14 additions & 0 deletions autogalaxy/ellipse/fit_ellipse.py
Original file line number Diff line number Diff line change
@@ -1,3 +1,17 @@
"""
Fit isophotal ellipses to a 2D image dataset.

`FitEllipse` uses a single `Ellipse` (plus optional `EllipseMultipole` perturbations) to fit an imaging
dataset. Rather than convolving a model image with a PSF, the fit works by:

1. Computing the (y, x) sample points distributed around the ellipse's perimeter.
2. Interpolating the image data and noise-map at those sample points.
3. Computing residuals between the interpolated data values and the mean intensity along the ellipse.

This is the classical isophote-fitting approach used in tools such as IRAF/ELLIPSE and galfit, and is
appropriate for measuring galaxy morphology, position angles, axis ratios, and multipole perturbations
directly from imaging data without fitting a parametric light profile model.
"""
import numpy as np
from typing import List, Optional

Expand Down
12 changes: 12 additions & 0 deletions autogalaxy/ellipse/model/analysis.py
Original file line number Diff line number Diff line change
@@ -1,3 +1,15 @@
"""
`AnalysisEllipse` — the **PyAutoFit** `Analysis` class for fitting isophotal ellipse models to imaging data.

This module provides `AnalysisEllipse`, which implements `log_likelihood_function` by:

1. Extracting the ellipse (and optional multipoles) from the model instance.
2. Constructing a `FitEllipse` object.
3. Returning the `figure_of_merit` of the fit.

Unlike `AnalysisImaging`, this class does not use PSF convolution or linear inversions. It directly fits
the isophotal structure of the image via interpolation along the ellipse perimeter.
"""
import logging
import numpy as np
from typing import List, Optional
Expand Down
Loading