Implemented the Fourier Normalizing Radial Gradient Filter

changelog/17.feature.rst

@@ -0,0 +1 @@
+Added a new function (`sunkit_image.radial.fnrgf`) to normalize the radial brightness gradient using a Fourier approximation.

docs/code_ref/index.rst

@@ -8,5 +8,5 @@ Code Reference
    :maxdepth: 2
 
    sunkit_image
-   offlimb_enhance
+   radial
    utils

docs/code_ref/radial.rst

@@ -0,0 +1,7 @@
+******
+radial
+******
+
+This package implements radial enhancement routines for solar physics data.
+
+.. automodapi:: sunkit_image.radial

examples/radial_gradient_filters.py

@@ -0,0 +1,66 @@
+"""
+=======================
+Radial Gradient Filters
+=======================
+
+This example applies both the normalizing radial gradient (`sunkit_image.radial.nrgf`) filter and Fourier
+normalizing radial gradient filter (`sunkit_image.radial.fnrgf`) to a sunpy map.
+"""
+# sphinx_gallery_thumbnail_number = 3
+
+import numpy as np
+import matplotlib.pyplot as plt
+
+import astropy.units as u
+
+import sunpy.map
+import sunpy.data.sample
+
+import sunkit_image.radial as radial
+from sunkit_image.utils import equally_spaced_bins
+
+###########################################################################
+# Sunpy's sample data contain a number of suitable FITS files for this purpose.
+aia_map = sunpy.map.Map(sunpy.data.sample.AIA_171_IMAGE)
+
+# The original image is plotted to showcase the difference.
+fig = plt.figure()
+ax = plt.subplot(projection=aia_map)
+aia_map.plot()
+
+###########################################################################
+# Both the NRGF and FNRGF work on radial segments above their application radius.
+# Here we create those segments radial segments. Each segment created will be of
+# equal dimensions radially. The distance between 1 solar radii and 2 solar radii
+# is divided into 100 equal parts by the following two lines.
+radial_bin_edges = equally_spaced_bins()
+radial_bin_edges *= u.R_sun
+
+# The NRGF filter is applied after it.
+out1 = radial.nrgf(aia_map, radial_bin_edges)
+
+# The NRGF filtered map is plotted.
+# The image seems a little washed out so you may need to change some plotting settings
+# for a clearer output.
+fig = plt.figure()
+ax = plt.subplot(projection=out1)
+out1.plot()
+
+###########################################################################
+# We will need to work out  a few parameters for the FNRGF.
+# Order is the number of Fourier coefficients to be used in the approximation.
+# The attentuation coefficient are calculated to be linearly decreasing, you should
+# choose them according to your requirements.
+order = 20
+attenuation_coefficients = radial.set_attenuation_coefficients(order)
+
+# The FNRGF filter is applied after it.
+out2 = radial.fnrgf(aia_map, radial_bin_edges, order, attenuation_coefficients)
+
+# The FNRGF filtered map is plotted.
+fig = plt.figure()
+ax = plt.subplot(projection=out2)
+out2.plot()
+
+# All the figures are plotted.
+plt.show()

sunkit_image/conftest.py

@@ -4,7 +4,6 @@
 import tempfile
 import warnings
 import importlib
-from sys import version_info
 
 import pytest