clusters/halo: Fix load halos data; fix save halos catalog

The "template" item should be removed before convert the halos data into a
Pandas DataFrame to be saved.

1 files changed, 28 insertions, 27 deletions

diff --git a/fg21sim/extragalactic/clusters/main.py b/fg21sim/extragalactic/clusters/main.py
index f16a203..70d5e6b 100644
--- a/fg21sim/extragalactic/clusters/main.py
+++ b/fg21sim/extragalactic/clusters/main.py
@@ -23,7 +23,8 @@ from .psformalism import PSFormalism
 from .formation import ClusterFormation
 from .halo import RadioHalo
 from ...share import CONFIGS, COSMO
-from ...utils.io import dataframe_to_csv, csv_to_dataframe, pickle_dump
+from ...utils.io import (dataframe_to_csv, csv_to_dataframe,
+                         pickle_dump, pickle_load)
 from ...utils.ds import dictlist_to_dataframe
 from ...utils.convert import JyPerPix_to_K
 from ...sky import get_sky
@@ -314,6 +315,31 @@ class GalaxyClusters:
             hdict["Tb_mean"] = Tb_mean  # [K]
         logger.info("Done calculate the radio emissions.")
 
+    def _draw_halos(self):
+        """
+        Draw the template images for each halo, and cache them for
+        simulating the superimposed halos at requested frequencies.
+
+        NOTE
+        ----
+        The drawn template images are append to the dictionaries of
+        the corresponding halo within the ``self.halos``.
+        The templates are normalized to have *mean* value of 1.
+        """
+        num = len(self.halos)
+        logger.info("Draw template images for %d halos ..." % num)
+        i = 0
+        for hdict in self.halos:
+            i += 1
+            if i % 100 == 0:
+                logger.info("[%d/%d] %.1f%% ..." % (i, num, 100*i/num))
+            theta_e = hdict["angular_radius"] / self.sky.pixelsize
+            rprofile = helper.halo_rprofile(re=theta_e)
+            template = helper.draw_halo(rprofile, felong=hdict["felong"],
+                                        rotation=hdict["rotation"])
+            hdict["template"] = template
+        logger.info("Done drawn halo template images.")
+
     def _save_halos_catalog(self, outfile=None):
         """
         Convert the halos data (``self.halos``) into a Pandas DataFrame
@@ -325,7 +351,7 @@ class GalaxyClusters:
         logger.info("Converting halos data to be a Pandas DataFrame ...")
         keys = list(self.halos[0].keys())
         # Ignore the ``gamma`` and ``n_e`` items
-        for k in ["gamma", "n_e"]:
+        for k in ["gamma", "n_e", "template"]:
             keys.remove(k)
         halos_df = dictlist_to_dataframe(self.halos, keys=keys)
         dataframe_to_csv(halos_df, outfile, clobber=self.clobber)
@@ -341,31 +367,6 @@ class GalaxyClusters:
             outfile = self.halos_data_dumpfile
         pickle_dump(self.halos, outfile=outfile, clobber=self.clobber)
 
-    def _draw_halos(self):
-        """
-        Draw the template images for each halo, and cache them for
-        simulating the superimposed halos at requested frequencies.
-
-        NOTE
-        ----
-        The drawn template images are append to the dictionaries of
-        the corresponding halo within the ``self.halos``.
-        The templates are normalized to have *mean* value of 1.
-        """
-        num = len(self.halos)
-        logger.info("Draw template images for %d halos ..." % num)
-        i = 0
-        for hdict in self.halos:
-            i += 1
-            if i % 100 == 0:
-                logger.info("[%d/%d] %.1f%% ..." % (i, num, 100*i/num))
-            theta_e = hdict["angular_radius"] / self.sky.pixelsize
-            rprofile = helper.halo_rprofile(re=theta_e)
-            template = helper.draw_halo(rprofile, felong=hdict["felong"],
-                                        rotation=hdict["rotation"])
-            hdict["template"] = template
-        logger.info("Done drawn halo template images.")
-
     def _outfilepath(self, frequency, **kwargs):
         """
         Generate the path/filename to the output file for writing