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Никита Тырин
2025-05-08 14:42:39 +03:00
parent 3a6927c180
commit 84c339d556
9 changed files with 434 additions and 68 deletions
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247
views.py
View File

@@ -7,7 +7,9 @@ import astropy.units as u
from astropy.coordinates import SkyCoord
import scipy.special as sp
from astropy.stats import poisson_conf_interval
from django.db.models import Sum
from rest_framework.views import APIView
from rest_framework.response import Response
from rest_framework import status
@@ -15,41 +17,129 @@ from rest_framework import status
from django.shortcuts import get_object_or_404
from axc_ul.models import Pixel
#from axc_ul_server.axc_ul.serializers import PixelSerializer
from .serializers import PixelSerializer
class PixelDetailView(APIView):
# SURVEY PARAMETER PARSER
# **************************************************************
def parse_survey_param(raw: str) -> list[int]:
surveys = set()
for part in raw.split(","):
if "-" in part:
start, end = part.split("-", 1)
surveys.update(range(int(start), int(end) + 1))
else:
surveys.add(int(part))
return sorted(surveys)
# PIXEL VIEW (MOSTLY FOR TESTING)
# **************************************************************
class PixelAggregateView(APIView):
"""
API endpoint that returns the pixel data (counts, exposure, rate)
for a given survey number and hpid.
GET /pixel-aggregate/?pixel=<hpid>&survey=<spec>
- <spec> can be a single number (e.g. 5),
a CSV list (e.g. 1,3,7) or a hyphen range (e.g. 2-5).
Returns sums of counts & exposure across the selected surveys.
"""
def get(self, request, hpid):
# Get the survey using the survey_number field.
# survey = get_object_or_404(Survey, number=survey_number)
def get(self, request):
# GET PARAMETERS FROM THE QUERY
# **************************************************************
raw_pixel = request.query_params.get("pixel")
raw_survey = request.query_params.get("survey")
# 400 BADREQUEST
# **************************************************************
if raw_pixel is None or raw_survey is None:
return Response(
{"detail": "Both `pixel` and `survey` parameters are required."},
status=status.HTTP_400_BAD_REQUEST
)
# FILTER THE INPUTS
# **************************************************************
try:
hpid = int(raw_pixel)
except ValueError:
return Response(
{"detail": "`pixel` must be an integer."},
status=status.HTTP_400_BAD_REQUEST
)
try:
survey_numbers = parse_survey_param(raw_survey)
except ValueError:
return Response(
{"detail": "Malformed `survey`; use N, N,M or N-M formats."},
status=status.HTTP_400_BAD_REQUEST
)
# FILTER AND AGGREGATE
# **************************************************************
qs = Pixel.objects.filter(
hpid=hpid,
survey__number__in=survey_numbers
)
if not qs.exists():
# no matching pixel(s) → 404
get_object_or_404(Pixel, hpid=hpid, survey__number__in=survey_numbers)
result = qs.aggregate(
total_counts=Sum("counts"),
total_exposure=Sum("exposure")
)
# RETURN THE SUMS
# **************************************************************
return Response(result, status=status.HTTP_200_OK)
# class PixelDetailView(APIView):
# """
# API endpoint that returns the pixel data (counts, exposure, rate)
# for a given hpid.
# """
# def get(self, request, hpid):
# # Get the survey using the survey_number field.
# # survey = get_object_or_404(Survey, number=survey_number)
# Get the pixel corresponding to the survey and hpid.
pixel = get_object_or_404(Pixel, hpid=hpid)
# # Get the pixel corresponding to the survey and hpid.
# pixel = get_object_or_404(Pixel, hpid=hpid)
# Serialize the pixel data to JSON.
serializer = PixelSerializer(pixel)
return Response(serializer.data, status=status.HTTP_200_OK)
# # Serialize the pixel data to JSON.
# serializer = PixelSerializer(pixel)
# return Response(serializer.data, status=status.HTTP_200_OK)
# UPPER LIMIT COMPUTATION VIEW
# **************************************************************
class UpperLimitView(APIView):
"""
Calculate and return upper limits (UL, CRUL, FLUL) based on provided RA, DEC, and CL parameters.
Calclassic_count_ulate and return upper limits (UL, CRUL, FLUL) based on provided RA, DEC, and CL parameters.
Args:
request: HTTP GET request containing 'ra', 'dec', and 'cl' query parameters.
Returns:
Response object with JSON data containing calculated UL, CRUL, and FLUL values.
Response object with JSON data containing calclassic_count_ulated UL, CRUL, and FLUL values.
Raises:
ValueError if provided parameters are invalid.
"""
def get(self, request):
# GET PARAMETERS FROM THE REQUEST
# **************************************************************
try:
ra = float(request.query_params.get('ra'))
dec = float(request.query_params.get('dec'))
@@ -59,24 +149,48 @@ class UpperLimitView(APIView):
{"error": "Invalud parameters, provide RA, DEC, and CL"},
status = status.HTTP_400_BAD_REQUEST
)
# ── NEW: pull & parse survey selection ──
raw_survey = request.query_params.get('survey')
if raw_survey is None:
return Response(
{"error": "Missing required `survey` parameter (e.g. ?survey=1,3-5)"},
status=status.HTTP_400_BAD_REQUEST
)
try:
survey_numbers = parse_survey_param(raw_survey)
except ValueError:
return Response(
{"error": "Malformed `survey`; use formats like 1, 2-5, or 1,3-4"},
status=status.HTTP_400_BAD_REQUEST
)
# hp = HEALPix(
# nside = 4096,
# order = 'ring',
# frame = 'icrs'
# )
# CREATE SKYCOORD, CONVERT TO GALACTIC BECAUSE THE HEALPIX
# MAP ITSELF WAS MADE IN GALACTIC COORDINATES
# **************************************************************
src_coord = SkyCoord(
ra, dec, unit = 'deg', frame = 'icrs'
)
gal = src_coord.galactic
src_vec = hp.ang2vec(gal.l.deg, gal.b.deg, lonlat = True)
aperture_radius = 50 # radius of the aperture in arc seconds
# DEFINE APERTURE AND ANNULUS RADII
# **************************************************************
aperture_radius = 71 # radius of the aperture in arc seconds
# HPD ~48 arcseconds
# 90% ~100 arcseconds
annulus_inner = 100 # 2 * aperture_radius
annulus_outer = 200 # 4 * aperture_radius
annulus_inner = 142 # 2 * aperture_radius
annulus_outer = 284 # 4 * aperture_radius
# FETCH PIXEL DATA DEFINED VIA HP.QUERY_DISC (INCLUSIVE=FALSE)
# **************************************************************
source_pixel_list = hp.query_disc(
nside = 4096,
@@ -108,10 +222,26 @@ class UpperLimitView(APIView):
]
source_pixels = Pixel.objects.filter(hpid__in = source_pixel_list)
source_pixels = Pixel.objects.filter(
hpid__in = source_pixel_list,
survey__number__in = survey_numbers
)
annulus_pixels = Pixel.objects.filter(hpid__in = annulus_pixel_list)
annulus_pixels = Pixel.objects.filter(
hpid__in = annulus_pixel_list,
survey__number__in = survey_numbers
)
if not source_pixels.exists() and not annulus_pixels.exists():
return Response(
{"detail": "No pixel data for the given survey selection."},
status=status.HTTP_404_NOT_FOUND
)
# COMPUTE COUNTS, BACKGROUND ESTIMATE, EXPOSURE
# **************************************************************
N = sum(obj.counts for obj in source_pixels)
@@ -127,26 +257,78 @@ class UpperLimitView(APIView):
t = tsum / Nnpix
# CONSTANTS
# **************************************************************
EEF = .9 # eclosed energy fraction, .5 for hpd, .9 for w90
ECF = 4e-11 # energy conversion factor
UL = (
sp.gammaincinv(
N + 1,
confidence_level * sp.gammaincc(N + 1, B) + sp.gammainc(N + 1, B)
) - B
) # count upper limit
CRUL = UL / t / EEF # count rate upper limit
# BAYESIAN IMPLEMENTATION VIA POISSON_CONF_INTERVAL
# **************************************************************
low, high = poisson_conf_interval(
n = N,
background = B,
interval = 'kraft-burrows-nousek',
confidence_level=confidence_level
)
bayesian_count_ul = high
bayesian_count_ll = low
bayesian_rate_ul = bayesian_count_ul / t / EEF # count rate limits
bayesian_rate_ll = bayesian_count_ll / t / EEF
bayesian_flux_ul = bayesian_rate_ul * ECF # flux limits
bayesian_flux_ll = bayesian_rate_ll * ECF
# CLASSICAL IMPLEMENTATION VIA GAMMAINCCINV
# ****************************************************************
classic_count_ul = sp.gammainccinv(N+1, 1 - confidence_level) - B
classic_count_ll = sp.gammainccinv(N, confidence_level) - B
classic_count_ll = max(classic_count_ll, 0)
classic_rate_ul = classic_count_ul / t / EEF # count rate limits
classic_rate_ll = classic_count_ll / t / EEF
classic_flux_ul = classic_rate_ul * ECF # flux limits
classic_flux_ll = classic_rate_ll * ECF
# FLUX ESTIMATION
# ****************************************************************
S = N - B # counts as simply counts within aperture
# with the background estimate subtracted
CR = S / t / EEF # count rate
FL = CR * ECF # conversion to flux
Flux = max(FL, 0) # flux cannot be lower than zero
FLUL = CRUL * ECF # flux upper limit
return Response({
'UpperLimit' : UL,
'CountRateUpperLimit' : CRUL,
'FluxUpperLimit' : FLUL,
'ClassicUpperLimit' : classic_count_ul,
'ClassicLowerLimit' : classic_count_ll,
'ClassicCountRateUpperLimit' : classic_rate_ul,
'ClassicCountRateLowerLimit' : classic_rate_ll,
'ClassicFluxUpperLimit' : classic_flux_ul,
'ClassicFluxLowerLimit' : classic_flux_ll,
'BayesianUpperLimit' : bayesian_count_ul,
'BayesianLowerLimit' : bayesian_count_ll,
'BayesianCountRateUpperLimit' : bayesian_rate_ul,
'BayesianCountRateLowerLimit' : bayesian_rate_ll,
'BayesianFluxUpperLimit' : bayesian_flux_ul,
'BayesianFluxLowerLimit' : bayesian_flux_ll,
'FluxEstimate' : Flux,
'N' : N,
'Nnpix' : Nnpix,
'Bcounts' : Bcounts,
@@ -154,4 +336,5 @@ class UpperLimitView(APIView):
'B' : B,
'tsum' : tsum,
't' : t
}, status=status.HTTP_200_OK)