Merge branch 'thomaswmorris:master' into master

Author: aileench3n

docs/source/tutorials/maximum-likelihood-mapper.ipynb

@@ -17,10 +17,10 @@
     "import maria\n",
     "from maria.io import fetch\n",
     "\n",
-    "input_map = maria.map.load(fetch(\"maps/cluster2.fits\"), nu=150e9)\n",
+    "input_map = maria.map.load(fetch(\"maps/cluster1.fits\"), nu=150e9).to(\"uK_RJ\")\n",
     "input_map.data *= 2e1\n",
     "\n",
-    "input_map[..., 256:-256, 256:-256].to(\"K_RJ\").plot(cmap=\"cmb\")\n",
+    "input_map.plot(cmap=\"cmb\")\n",
     "print(input_map)"
    ]
   },
@@ -33,9 +33,9 @@
     "from maria import Planner\n",
     "\n",
     "planner = Planner(target=input_map, site=\"cerro_toco\", constraints={\"el\": (70, 90)})\n",
-    "plans = planner.generate_plans(total_duration=900, \n",
-    "                               max_chunk_duration=900, \n",
-    "                               sample_rate=50,\n",
+    "plans = planner.generate_plans(total_duration=3600, \n",
+    "                               max_chunk_duration=3600, \n",
+    "                               sample_rate=25,\n",
     "                               scan_options={\"radius\": input_map.width.deg / 2})\n",
     "\n",
     "plans[0].plot()\n",
@@ -58,7 +58,7 @@
     "    knee=1e1, \n",
     "    gain_error=2e-2)\n",
     "\n",
-    "array = {\"field_of_view\": 0.2, \n",
+    "array = {\"field_of_view\": 0.15, \n",
     "         \"beam_spacing\": 1.25,\n",
     "         \"primary_size\": 25, \n",
     "         \"shape\": \"circle\",\n",
@@ -107,8 +107,8 @@
     "from maria.mappers import MaximumLikelihoodMapper\n",
     "\n",
     "ml_mapper = MaximumLikelihoodMapper(tods=tods, \n",
-    "                                    width=0.75 * input_map.width.deg,\n",
-    "                                    height=0.75 * input_map.height.deg,\n",
+    "                                    width=0.8 * input_map.width.deg,\n",
+    "                                    height=0.8 * input_map.height.deg,\n",
     "                                    resolution=10 * input_map.resolution.deg,\n",
     "                                    units=\"mK_RJ\")\n",
     "print(f\"{ml_mapper.loss() = }\")"

maria/mappers/ml_mapper.py

@@ -98,7 +98,7 @@ def __init__(
                 "remove_modes": {"modes_to_remove": 1},
                 "remove_spline": {"knot_spacing": 20, "remove_el_gradient": True},
             },
-            map_postprocessing={"gaussian_filter": {"sigma": 2}},
+            # map_postprocessing={"gaussian_filter": {"sigma": 2}},
             progress_bars=False,
         )
 

maria/sim/map.py

@@ -96,6 +96,8 @@ def _sample_maps(self, obs):
             # ideally we would do this for each nu bin, but that's slow
             smoothed_map = self.map.smooth(fwhm=band_fwhm)
 
+            logger.debug(f"Convolved map with beam width {band_fwhm} for band {band.name}")
+
             for channel_index, (nu_min, nu_max) in enumerate(self.map.nu_bin_bounds):
                 channel_s = ttime.monotonic()
                 channel_map = smoothed_map.to("K_RJ", band=band)[:, [channel_index]]

maria/spectrum/atmosphere.py

@@ -70,9 +70,9 @@ def __repr__(self):
   altitude: {Quantity(self.altitude, "m")}"""
 
     def _interpolate_quantity(self, quantity, nu, pwv=None, base_temperature=None, elevation=None):
-        pwv = pwv or np.median(self.side_zenith_pwv)
-        base_temperature = base_temperature or np.median(self.side_base_temperature)
-        elevation = elevation or np.radians(45)
+        pwv = pwv if pwv is not None else np.median(self.side_zenith_pwv)
+        base_temperature = base_temperature if base_temperature is not None else np.median(self.side_base_temperature)
+        elevation = elevation if elevation is not None else np.radians(45)
 
         min_pwv = self.side_zenith_pwv.min()
         max_pwv = self.side_zenith_pwv.max()