Update interpolation code to pyirf v0.10 API

environment.yml

@@ -33,5 +33,5 @@ dependencies:
   - seaborn
   - ctapipe_io_lst=0.22
   - pytest
-  - pyirf=0.8
+  - pyirf~=0.10.0
 

lstchain/high_level/interpolate.py

@@ -14,10 +14,10 @@
 )
 from pyirf.interpolation import (
     GridDataInterpolator,
-    interpolate_effective_area_per_energy_and_fov,
-    interpolate_energy_dispersion,
-    interpolate_psf_table,
-    interpolate_rad_max,
+    EnergyDispersionEstimator,
+    EffectiveAreaEstimator,
+    PSFTableEstimator,
+    RadMaxEstimator,
 )
 from scipy.spatial import Delaunay, distance, QhullError
 
@@ -34,6 +34,7 @@
 
 log = logging.getLogger(__name__)
 
+
 def interp_params(params_list, data):
     """
     From a given list of angular parameters, to be used for interpolation,
@@ -361,8 +362,10 @@
     ----------
     .. [1] https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.griddata.html
     """
-    interp = GridDataInterpolator(grid_points=grid_points, params=gh_cuts)
-    gh_cuts_interp = interp(target_point, method=method)
+    interp = GridDataInterpolator(
+        grid_points=grid_points, params=gh_cuts, method=method
+    )
+    gh_cuts_interp = interp(target_point)
 
     return gh_cuts_interp
 
@@ -402,8 +405,10 @@
     ----------
     .. [1] https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.griddata.html
     """
-    interp = GridDataInterpolator(grid_points=grid_points, params=al_cuts)
-    al_cuts_interp = interp(target_point, method=method)
+    interp = GridDataInterpolator(
+        grid_points=grid_points, params=al_cuts, method=method
+    )
+    al_cuts_interp = interp(target_point)
 
     return al_cuts_interp
 
@@ -507,12 +512,11 @@
         e_true = np.append(temp_irf["ENERG_LO"][0], temp_irf["ENERG_HI"][0][-1])
         fov_off = np.append(temp_irf["THETA_LO"][0], temp_irf["THETA_HI"][0][-1])
 
-        aeff_interp = interpolate_effective_area_per_energy_and_fov(
-            effective_area=effarea_list,
+        aeff_estimator = EffectiveAreaEstimator(
             grid_points=irf_pars_sel,
-            target_point=interp_pars_sel,
-            method=interp_method
+            effective_area=effarea_list,
         )
+        aeff_interp = aeff_estimator(interp_pars_sel)
 
         aeff_hdu_interp = create_aeff2d_hdu(
             effective_area=aeff_interp.T[0],
@@ -540,13 +544,12 @@
         e_migra = np.append(temp_irf["MIGRA_LO"][0], temp_irf["MIGRA_HI"][0][-1])
         fov_off = np.append(temp_irf["THETA_LO"][0], temp_irf["THETA_HI"][0][-1])
 
-        edisp_interp = interpolate_energy_dispersion(
-            migra_bins=e_migra,
-            edisps=edisp_list,
+        edisp_estimator = EnergyDispersionEstimator(
             grid_points=irf_pars_sel,
-            target_point=interp_pars_sel,
-            quantile_resolution=1e-3
+            migra_bins=e_migra,
+            energy_dispersion=edisp_list,
         )
+        edisp_interp = edisp_estimator(interp_pars_sel)
 
         edisp_hdu_interp = create_energy_dispersion_hdu(
             energy_dispersion=edisp_interp[0],
@@ -575,7 +578,7 @@
             gh_cuts=gh_cuts_list,
             grid_points=irf_pars_sel,
             target_point=interp_pars_sel,
-            method=interp_method
+            method=interp_method,
         )
 
         gh_header = fits.Header()
@@ -599,12 +602,11 @@
         radmax_list = load_irf_grid(irfs, extname="RAD_MAX", interp_col="RAD_MAX")
         temp_irf = QTable.read(irfs[0], hdu="RAD_MAX")
 
-        rad_max_interp = interpolate_rad_max(
-            rad_max=radmax_list,
+        rad_max_estimator = RadMaxEstimator(
             grid_points=irf_pars_sel,
-            target_point=interp_pars_sel,
-            method=interp_method
+            rad_max=radmax_list,
         )
+        rad_max_interp = rad_max_estimator(interp_pars_sel)
 
         temp_irf["RAD_MAX"] = rad_max_interp[0].T[np.newaxis, ...] * u.deg
 
@@ -661,13 +663,13 @@
             src_bins = np.append(temp_irf["RAD_LO"][0], temp_irf["RAD_HI"][0][-1])
             fov_off = np.append(temp_irf["THETA_LO"][0], temp_irf["THETA_HI"][0][-1])
 
-            psf_interp = interpolate_psf_table(
-                source_offset_bins=src_bins,
-                psfs=psf_list,
+            psf_estimator = PSFTableEstimator(
                 grid_points=irf_pars_sel,
-                target_point=interp_pars_sel,
-                quantile_resolution=1e-3,
+                source_offset_bins=src_bins,
+                psf=psf_list,
             )
+            psf_interp = psf_estimator(interp_pars_sel)
+
             psf_hdu_interp = create_psf_table_hdu(
                 psf=psf_interp[0],
                 true_energy=e_true,

lstchain/io/io.py

@@ -977,7 +977,8 @@ def read_mc_dl2_to_QTable(filename):
         energy_max=simu_info.energy_range_max,
         max_impact=simu_info.max_scatter_range,
         spectral_index=simu_info.spectral_index,
-        viewcone=simu_info.max_viewcone_radius
+        viewcone_min=simu_info.min_viewcone_radius,
+        viewcone_max=simu_info.max_viewcone_radius
     )
 
     events = pd.read_hdf(filename, key=dl2_params_lstcam_key)

setup.py

@@ -54,7 +54,7 @@ def find_scripts(script_dir, prefix):
         'numpy',
         'pandas',
         'protobuf~=3.20.0',
-        'pyirf~=0.8.0',
+        'pyirf~=0.10.0',
         'scipy>=1.8',
         'seaborn',
         'scikit-learn~=1.2',