code formatting
This commit is contained in:
@@ -7,19 +7,19 @@
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from django.core.management.base import BaseCommand
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from django.db import transaction
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from uplim.models import Pixel, CatalogSource
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import pandas as pd
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import healpy as hp
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import numpy as np
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from astropy.coordinates import SkyCoord
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from uplim.models import Pixel, CatalogSource
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from itertools import islice
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from datetime import datetime
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BATCH_SIZE=900
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BATCH_SIZE = 900
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def batch(iterable, size):
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iterable = iter(iterable)
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@@ -28,157 +28,165 @@ def batch(iterable, size):
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if not chunk:
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break
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yield chunk
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class Command(BaseCommand):
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help = "Set the 'contaminated' flag for all pixels based on the fluxes in the provided catalog."
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# COMMAND LINE ARGUMENTS
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# **********************
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def add_arguments(self, parser):
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parser.add_argument(
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'--catalog',
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type=str,
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required=False,
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help='Path to the catalog.dat file'
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"--catalog", type=str, required=False, help="Path to the catalog.dat file"
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)
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# parser.add_argument(
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# '--survey',
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# type=int,
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# required=False,
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# help='integer number of the survey to set the flag for'
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# )
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parser.add_argument(
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'--reset',
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action='store_true',
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"--reset",
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action="store_true",
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default=False,
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help='Reset the contamination flag across all pixels back to False.'
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help="Reset the contamination flag across all pixels back to False.",
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)
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def handle(self, *args, **options):
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# RESET BEHAVIOR: SET CONTAMINATION FLAG TO FALSE FOR ALL PIXELS
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# **************************************************************
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if options['reset']:
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if options["reset"]:
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self.stdout.write("Resetting the contamination flag...")
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Pixel.objects.update(contaminated = False)
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Pixel.objects.update(contaminated=False)
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self.stdout.write("Done")
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return
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if not options['catalog']:
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if not options["catalog"]:
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self.stdout.write("No catalog file provided, exiting")
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return
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catalog_file = options['catalog']
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catalog_file = options["catalog"]
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self.stdout.write(f"Catalog file:\t{catalog_file}")
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# READ THE CATALOG FILE USING PANDAS READ_FWF
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# *******************************************
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# Define column positions based on the byte ranges
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# Define column positions based on the byte ranges
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colspecs = [
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(0, 4), # SrcID (1-4)
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(5, 26), # Name (6-26)
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(0, 4), # SrcID (1-4)
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(5, 26), # Name (6-26)
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(27, 37), # RAdeg (28-37)
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(38, 48), # DEdeg (39-48)
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(49, 55), # ePos (50-55)
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(56, 63), # Signi (57-63)
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(64, 76), # Flux (65-76)
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(77, 89), # e_Flux (78-89)
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(90, 118), # CName (91-118)
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(119, 120),# NewXray (120)
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(121, 134) # Type (122-134)
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(90, 118), # CName (91-118)
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(119, 120), # NewXray (120)
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(121, 134), # Type (122-134)
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]
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# Define column names
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colnames = [
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"SrcID", "Name", "RAdeg", "DEdeg", "ePos", "Signi", "Flux",
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"e_Flux", "CName", "NewXray", "Type"
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"SrcID",
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"Name",
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"RAdeg",
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"DEdeg",
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"ePos",
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"Signi",
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"Flux",
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"e_Flux",
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"CName",
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"NewXray",
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"Type",
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]
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# Read the file using the fixed-width format
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catalog = pd.read_fwf(catalog_file, colspecs=colspecs, names=colnames)
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for col in ['Name', 'CName', 'Type']:
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catalog[col] = catalog[col].fillna('')
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for col in ["Name", "CName", "Type"]:
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catalog[col] = catalog[col].fillna("")
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self.stdout.write(str(catalog.head()))
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# LOAD THE CATALOG INTO THE DATABASE
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# **********************************
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existing_srcids = set(
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CatalogSource.objects.values_list('srcid', flat=True)
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)
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existing_srcids = set(CatalogSource.objects.values_list("srcid", flat=True))
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to_create = []
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for _, row in catalog.iterrows():
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srcid = int(row['SrcID'])
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srcid = int(row["SrcID"])
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if srcid in existing_srcids:
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continue
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to_create.append(
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CatalogSource(
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srcid = srcid,
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name = row['Name'].strip(),
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ra_deg = float(row['RAdeg']),
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dec_deg = float(row['DEdeg']),
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pos_error = float(row['ePos']),
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significance = float(row['Signi']),
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flux = float(row['Flux']),
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flux_error = float(row['e_Flux']),
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catalog_name = row['CName'].strip(),
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new_xray = bool(int(row['NewXray'])),
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source_type = row['Type'].strip()
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srcid=srcid,
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name=row["Name"].strip(),
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ra_deg=float(row["RAdeg"]),
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dec_deg=float(row["DEdeg"]),
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pos_error=float(row["ePos"]),
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significance=float(row["Signi"]),
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flux=float(row["Flux"]),
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flux_error=float(row["e_Flux"]),
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catalog_name=row["CName"].strip(),
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new_xray=bool(int(row["NewXray"])),
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source_type=row["Type"].strip(),
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)
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)
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if to_create:
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self.stdout.write(f'Inserting {len(to_create)} new catalog rows.')
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self.stdout.write(f"Inserting {len(to_create)} new catalog rows.")
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for chunk in batch(to_create, BATCH_SIZE):
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CatalogSource.objects.bulk_create(chunk, ignore_conflicts=True)
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self.stdout.write('Catalog update complete.')
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self.stdout.write("Catalog update complete.")
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else:
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self.stdout.write('All catalog rows already exist in the database.')
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self.stdout.write("All catalog rows already exist in the database.")
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# hard coded nside and flux-radius mapping
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# maybe change that
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nside = 4096
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npix = hp.nside2npix(nside)
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flux_bins = [0, 125, 250, 2000, 20000, np.inf] # define bin edges
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mask_radii_deg = [ 0.06, 0.15, 0.5, 0.9, 2.5 ] # corresponding mask radii in degrees
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flux_bins = [0, 125, 250, 2000, 20000, np.inf] # define bin edges
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mask_radii_deg = [
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0.06,
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0.15,
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0.5,
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0.9,
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2.5,
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] # corresponding mask radii in degrees
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# Convert mask radii from degrees to radians (required by query_disc)
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mask_radii = [np.radians(r) for r in mask_radii_deg]
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# Use pandas.cut to assign each source a bin index (0, 1, or 2)
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catalog['flux_bin'] = pd.cut(catalog['Flux'], bins=flux_bins, labels=False)
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catalog["flux_bin"] = pd.cut(catalog["Flux"], bins=flux_bins, labels=False)
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# manually add and change some sources
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manual_additions = pd.DataFrame(
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[
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{'RAdeg' : 279.9804336, 'DEdeg' : 5.0669542, 'flux_bin' : 3},
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{'RAdeg' : 266.5173685, 'DEdeg' : -29.1252321, 'flux_bin' : 3},
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{"RAdeg": 279.9804336, "DEdeg": 5.0669542, "flux_bin": 3},
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{"RAdeg": 266.5173685, "DEdeg": -29.1252321, "flux_bin": 3},
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]
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)
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catalog = pd.concat([catalog, manual_additions], ignore_index=True)
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catalog.loc[catalog['SrcID'] == 1101, 'flux_bin'] = 2
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catalog.loc[catalog["SrcID"] == 1101, "flux_bin"] = 2
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mask_array = np.ones(npix, dtype=bool)
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@@ -188,62 +196,58 @@ class Command(BaseCommand):
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# process each source in the catalog
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for _, row in catalog.iterrows():
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ra = row['RAdeg']
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dec = row['DEdeg']
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src_coord = SkyCoord(
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ra, dec, unit = 'deg', frame = 'icrs'
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)
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ra = row["RAdeg"]
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dec = row["DEdeg"]
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src_coord = SkyCoord(ra, dec, unit="deg", frame="icrs")
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gal = src_coord.galactic
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ra, dec = gal.l.deg, gal.b.deg
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flux_bin = row['flux_bin'] # 0, 1, or 2
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flux_bin = row["flux_bin"] # 0, 1, or 2
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# Get the corresponding mask radius (in radians) for this flux bin
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radius = mask_radii[flux_bin]
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# Convert (ra, dec) to HEALPix spherical coordinates
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theta = np.radians(90.0 - dec)
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phi = np.radians(ra)
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vec = hp.ang2vec(theta, phi)
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# Query all pixels within the given radius
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# 'inclusive=True' makes sure pixels on the edge are included
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pix_indices = hp.query_disc(nside, vec, radius, inclusive=True)
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# Mark these pixels as bad (False) in our mask
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mask_array[pix_indices] = False
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# Add the pixel indices to our set of masked pixels
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masked_pixels_set.update(pix_indices)
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# Convert the set of masked pixels to a sorted list.
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masked_pixels_list = sorted(list(masked_pixels_set))
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# print("Number of masked pixels:", len(masked_pixels_list))
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self.stdout.write("\nList ready, updating the database...")
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if not masked_pixels_list:
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self.stdout.write("No pixels marked as contaminated, exiting.")
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return
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total = len(masked_pixels_list)
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updated = 0
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self.stdout.write(f'\nUpdating contaminated flag in batches of {BATCH_SIZE}')
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self.stdout.write(f"\nUpdating contaminated flag in batches of {BATCH_SIZE}")
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for chunk in batch(masked_pixels_list, BATCH_SIZE):
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with transaction.atomic():
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Pixel.objects.filter(hpid__in=chunk).update(contaminated=True)
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updated += len(chunk)
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percentage = updated / total * 100
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timestamp = datetime.now().strftime("%H:%M:%S")
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self.stdout.write(f'[{timestamp}] {updated}/{total} ({percentage:.1f}%) updated')
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self.stdout.write(f'\n Marked {updated} pixels as contaminated.')
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self.stdout.write(
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f"[{timestamp}] {updated}/{total} ({percentage:.1f}%) updated"
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)
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self.stdout.write(f"\n Marked {updated} pixels as contaminated.")
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