Add function that checks fermi sources within the real 90% contour

skyreader/plot/plot.py

@@ -17,6 +17,7 @@
 from matplotlib import patheffects
 from matplotlib import pyplot as plt
 from matplotlib import text
+from matplotlib.path import Path as PolyPath
 from matplotlib.projections import projection_registry  # type: ignore[import]
 
 from .plotting_tools import (
@@ -280,6 +281,7 @@ def create_plot_zoomed(
         systematics=False,
         plot_bounding_box=False,
         plot_fermi_sources=False,
+        check_fermi_sources_box=False,
         circular=False,
         circular_err50=0.2,
         circular_err90=0.7,
@@ -589,7 +591,10 @@ def bounding_box(ra, dec, theta, phi):
         )
 
         if plot_fermi_sources:
-            sources_in_90 = self._save_sources_inside_90_box(ra, dec, ra_fermi_sources, dec_fermi_sources, name_fermi_sources, rectangular_errors["90"])
+            if check_fermi_sources_box:
+                sources_in_90 = self._save_sources_inside_90_box(ra, dec, ra_fermi_sources, dec_fermi_sources, name_fermi_sources, rectangular_errors["90"])
+            else:
+                sources_in_90 = self._save_sources_inside_90_contour(ra, dec, ra_fermi_sources, dec_fermi_sources, name_fermi_sources, contours_by_level[1])
 
         if plot_bounding_box:
             bounding_ras_list, bounding_decs_list = [], []
@@ -744,6 +749,32 @@ def bounding_box(ra, dec, theta, phi):
         if plot_fermi_sources:
             return sources_in_90
 
+    def _sources_inside_90_contour(self, ra_src, dec_src, name_src, contours):
+        # Convert inputs to numpy arrays
+        name_src = np.asarray(name_src)
+        ra_src = np.asarray(ra_src, dtype=float) % 360.0
+        dec_src = np.asarray(dec_src, dtype=float)
+        # Convert (RA, Dec) → spherical coordinates used by healpy
+        # theta = colatitude (0 = North pole, pi = South pole)
+        # phi   = longitude
+        src_theta = np.pi/2 - np.deg2rad(dec_src)
+        src_phi = np.deg2rad(ra_src)
+        # Combine coordinates into point array: (theta, phi)
+        points = np.column_stack([src_theta, src_phi])
+        # Initialize mask: False for all sources initially
+        inside_mask = np.zeros(len(points), dtype=bool)
+        for contour in contours:
+            # contour is (theta, phi)
+            contour_theta = contour[:, 0]
+            contour_phi = contour[:, 1]
+            # Build polygon in (theta, phi) space
+            poly = np.column_stack([contour_theta, contour_phi])
+            # Create a 2D path object for point-in-polygon test
+            path = PolyPath(poly)
+            # Update mask: mark sources inside this contour as True
+            inside_mask |= path.contains_points(points)
+        return name_src[inside_mask], ra_src[inside_mask], dec_src[inside_mask]
+
     def _sources_inside_90_box(self, ra_best_fit, dec_best_fit, ra_src, dec_src, name_src, rectangular_errors):
         ra_min = ra_best_fit + rectangular_errors["ra_minus"]
         ra_max = ra_best_fit + rectangular_errors["ra_plus"]
@@ -765,6 +796,49 @@ def _sources_inside_90_box(self, ra_best_fit, dec_best_fit, ra_src, dec_src, nam
         mask = ra_ok & dec_ok
         return name_src[mask], ra_src[mask], dec_src[mask]
 
+    def _save_sources_inside_90_contour(self, ra_best_fit, dec_best_fit, ra_src, dec_src, name_src, contour):
+        src_inside_90_name, src_inside_90_ra, src_inside_90_dec = self._sources_inside_90_contour(
+            ra_src,
+            dec_src,
+            name_src,
+            contour
+        )
+        ang_dist = np.zeros(len(src_inside_90_name), dtype=float)
+        for i in range(len(src_inside_90_name)):
+            ang_dist[i] = pyasl.getAngDist(
+                ra_best_fit,
+                dec_best_fit,
+                src_inside_90_ra[i],
+                src_inside_90_dec[i]
+            )
+        sources_in_90 = [
+            {
+                "name": name,
+                "ra": ra_src,
+                "dec": dec_src,
+                "ang_dist": dist
+            }
+            for name, ra_src, dec_src, dist in zip(
+                src_inside_90_name,
+                src_inside_90_ra,
+                src_inside_90_dec,
+                ang_dist
+            )
+        ]
+        sources_in_90_sorted = sorted(
+            sources_in_90,
+            key=lambda s: s["ang_dist"]
+        )
+        print("\nFermi sources inside 90% contour:\n")
+        for s in sources_in_90_sorted:
+            print(
+                f"- {s['name'].strip()}\n"
+                f"  RA: {s['ra']:.3f} deg\n"
+                f"  Dec: {s['dec']:.3f} deg\n"
+                f"  ang_dist: {s['ang_dist']:.3f} deg\n"
+            )
+        return sources_in_90
+
     def _save_sources_inside_90_box(self, ra_best_fit, dec_best_fit, ra_src, dec_src, name_src, rectangular_errors):
         src_inside_90_name, src_inside_90_ra, src_inside_90_dec = self._sources_inside_90_box(
             ra_best_fit,