diff options
| -rw-r--r-- | fg21sim/extragalactic/clusters/main.py | 55 |
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 |