Gain interpolation shape correction

nenupy/__init__.py

@@ -5,7 +5,7 @@
 __copyright__ = "Copyright 2023, nenupy"
 __credits__ = ["Alan Loh"]
 __license__ = "MIT"
-__version__ = "2.3.13"
+__version__ = "2.3.14"
 __maintainer__ = "Alan Loh"
 __email__ = "alan.loh@obspm.fr"
 

nenupy/astro/astro_tools.py

@@ -1181,8 +1181,9 @@ def hour_angle(self, fast_compute: bool = True) -> Longitude:
 # ============================================================= #
 # ----------------------- faraday_angle ----------------------- #
 # ============================================================= #
-@u.quantity_input
-def faraday_angle(frequency: u.Quantity[u.MHz], rotation_measure: u.Quantity[u.rad/u.m**2], inverse: bool = False):
+# @u.quantity_input
+# def faraday_angle(frequency: u.Quantity[u.MHz], rotation_measure: u.Quantity[u.rad/u.m**2], inverse: bool = False):
+def faraday_angle(frequency: u.Quantity, rotation_measure: u.Quantity, inverse: bool = False):
     """ Computes the Faraday rotation angle.
 
         :param frequency:

nenupy/instru/nenufar.py

@@ -130,9 +130,9 @@ def __getitem__(self, sky: Sky) -> np.ndarray:
         # Find the interpolated gain at the desired frequency
         #gain = self.interpolated_gain(self.healpix_coords, freqs)
         #gain = self.interpolated_gain((freqs, self.healpix_coords))
-        gain = self.interpolated_gain(freqs)
-        if gain.ndim == 1:
-            gain = gain.reshape((1, gain.size))
+        gain = self.interpolated_gain(freqs) # shape: (freq, pix_coord)
+        # if gain.ndim == 1:
+        #     gain = gain.reshape((1, gain.size))
 
         # Find the interpolated gain at the desired coordinates for each frequency
         gain = np.array([
@@ -145,8 +145,11 @@ def __getitem__(self, sky: Sky) -> np.ndarray:
             ) for gain_i in gain
         ])
 
+        if gain.ndim == 2:
+            # The time dimension is not yet included
+            gain = gain.reshape((1,) + gain.shape)
         # Return something shaped as (time, freq, coord)
-        return gain#np.moveaxis(gain, 0, 1)
+        return np.moveaxis(gain, 0, 1) # keep that!
         #return gain.reshape((1,) + gain.shape) # use with RegularGridInterpolator