code formatting
This commit is contained in:
412
views.py
412
views.py
@@ -4,25 +4,24 @@
|
||||
# search for pixels non-inclusively
|
||||
import healpy as hp
|
||||
import astropy.units as u
|
||||
from astropy.coordinates import SkyCoord, Angle
|
||||
import numpy as np
|
||||
|
||||
import scipy.special as sp
|
||||
|
||||
from astropy.coordinates import SkyCoord, Angle
|
||||
from astropy.stats import poisson_conf_interval
|
||||
|
||||
from django.db.models import Sum
|
||||
from django.shortcuts import get_object_or_404
|
||||
from rest_framework.views import APIView
|
||||
from rest_framework.response import Response
|
||||
from rest_framework import status
|
||||
|
||||
from django.shortcuts import get_object_or_404
|
||||
|
||||
from uplim.models import Pixel, CatalogSource
|
||||
|
||||
# SANITIZE RESPONSE DATA BEFORE JSON CONVERSION FOR DEBUGGING NANS
|
||||
# now NaNs are converted to 'null' beforehand
|
||||
# ****************************************************************
|
||||
|
||||
|
||||
def sanitize(obj):
|
||||
if isinstance(obj, dict):
|
||||
return {k: sanitize(v) for k, v in obj.items()}
|
||||
@@ -52,17 +51,17 @@ def parse_survey_param(raw):
|
||||
return sorted(surveys)
|
||||
|
||||
|
||||
|
||||
# PIXEL VIEW (MOSTLY FOR TESTING)
|
||||
# add healpix indices into the output
|
||||
# **************************************************************
|
||||
|
||||
|
||||
class PixelAggregateView(APIView):
|
||||
|
||||
def get(self, request):
|
||||
# GET PARAMETERS FROM THE QUERY
|
||||
# **************************************************************
|
||||
raw_pixel = request.query_params.get("pixel")
|
||||
raw_pixel = request.query_params.get("pixel")
|
||||
raw_survey = request.query_params.get("survey")
|
||||
|
||||
# 400 BADREQUEST
|
||||
@@ -70,7 +69,7 @@ class PixelAggregateView(APIView):
|
||||
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
|
||||
status=status.HTTP_400_BAD_REQUEST,
|
||||
)
|
||||
|
||||
# FILTER THE INPUTS
|
||||
@@ -80,7 +79,7 @@ class PixelAggregateView(APIView):
|
||||
except ValueError:
|
||||
return Response(
|
||||
{"detail": "`pixel` must be an integer."},
|
||||
status=status.HTTP_400_BAD_REQUEST
|
||||
status=status.HTTP_400_BAD_REQUEST,
|
||||
)
|
||||
|
||||
try:
|
||||
@@ -88,44 +87,33 @@ class PixelAggregateView(APIView):
|
||||
except ValueError:
|
||||
return Response(
|
||||
{"detail": "Malformed `survey`; use N, N,M or N-M formats."},
|
||||
status=status.HTTP_400_BAD_REQUEST
|
||||
status=status.HTTP_400_BAD_REQUEST,
|
||||
)
|
||||
|
||||
# FILTER AND AGGREGATE
|
||||
# **************************************************************
|
||||
qs = Pixel.objects.filter(
|
||||
hpid=hpid,
|
||||
survey__in=survey_numbers
|
||||
)
|
||||
|
||||
qs = Pixel.objects.filter(hpid=hpid, survey__in=survey_numbers)
|
||||
|
||||
if not qs.exists():
|
||||
# no matching pixel(s) → 404
|
||||
get_object_or_404(
|
||||
Pixel,
|
||||
hpid=hpid,
|
||||
survey__in=survey_numbers
|
||||
)
|
||||
get_object_or_404(Pixel, hpid=hpid, survey__in=survey_numbers)
|
||||
|
||||
aggregates = qs.aggregate(
|
||||
#pixel_hpid=hpid,
|
||||
#survey_number=survey_numbers,
|
||||
# pixel_hpid=hpid,
|
||||
# survey_number=survey_numbers,
|
||||
total_counts=Sum("counts"),
|
||||
total_exposure=Sum("exposure")
|
||||
total_exposure=Sum("exposure"),
|
||||
)
|
||||
|
||||
plusdata = {
|
||||
'pixel_hpid' : hpid,
|
||||
'surveys' : survey_numbers
|
||||
}
|
||||
|
||||
plusdata = {"pixel_hpid": hpid, "surveys": survey_numbers}
|
||||
|
||||
result = {**aggregates, **plusdata}
|
||||
|
||||
|
||||
# RETURN THE SUMS
|
||||
# **************************************************************
|
||||
return Response(result, status=status.HTTP_200_OK)
|
||||
|
||||
|
||||
|
||||
# UPPER LIMIT COMPUTATION VIEW
|
||||
# **************************************************************
|
||||
|
||||
@@ -134,317 +122,303 @@ class UpperLimitView(APIView):
|
||||
"""
|
||||
Calculate confidence bounds based on aperture photometry using classic and bayesian methods
|
||||
"""
|
||||
|
||||
def get(self, request):
|
||||
|
||||
|
||||
# GET PARAMETERS FROM THE REQUEST
|
||||
# **************************************************************
|
||||
|
||||
|
||||
try:
|
||||
ra = float(request.query_params.get('ra'))
|
||||
dec = float(request.query_params.get('dec'))
|
||||
confidence_level = float(request.query_params.get('cl'))
|
||||
ra = float(request.query_params.get("ra"))
|
||||
dec = float(request.query_params.get("dec"))
|
||||
confidence_level = float(request.query_params.get("cl"))
|
||||
except (TypeError, ValueError):
|
||||
return Response(
|
||||
{"error": "Invalud parameters, provide RA, DEC, and CL"},
|
||||
status = status.HTTP_400_BAD_REQUEST
|
||||
status=status.HTTP_400_BAD_REQUEST,
|
||||
)
|
||||
# ── NEW: pull & parse survey selection ──
|
||||
raw_survey = request.query_params.get('survey')
|
||||
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
|
||||
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
|
||||
)
|
||||
{"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'
|
||||
)
|
||||
|
||||
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)
|
||||
src_vec = hp.ang2vec(gal.l.deg, gal.b.deg, lonlat=True)
|
||||
|
||||
# DEFINE APERTURE AND ANNULUS RADII
|
||||
# **************************************************************
|
||||
|
||||
aperture_radius = 71 # radius of the aperture in arc seconds
|
||||
aperture_radius = 71 # radius of the aperture in arc seconds
|
||||
# HPD ~48 arcseconds
|
||||
# 90% ~100 arcseconds
|
||||
annulus_inner = 142 # 2 * aperture_radius
|
||||
annulus_outer = 284 # 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,
|
||||
vec = src_vec,
|
||||
inclusive = False,
|
||||
nest = False,
|
||||
radius = (aperture_radius * u.arcsecond).to(u.radian).value
|
||||
nside=4096,
|
||||
vec=src_vec,
|
||||
inclusive=False,
|
||||
nest=False,
|
||||
radius=(aperture_radius * u.arcsecond).to(u.radian).value,
|
||||
)
|
||||
|
||||
|
||||
inner_pixel_list = hp.query_disc(
|
||||
nside = 4096,
|
||||
vec = src_vec,
|
||||
inclusive = False,
|
||||
nest = False,
|
||||
radius = (annulus_inner * u.arcsecond).to(u.radian).value
|
||||
nside=4096,
|
||||
vec=src_vec,
|
||||
inclusive=False,
|
||||
nest=False,
|
||||
radius=(annulus_inner * u.arcsecond).to(u.radian).value,
|
||||
)
|
||||
|
||||
|
||||
outer_pixel_list = hp.query_disc(
|
||||
nside = 4096,
|
||||
vec = src_vec,
|
||||
inclusive = False,
|
||||
nest = False,
|
||||
radius = (annulus_outer * u.arcsecond).to(u.radian).value
|
||||
nside=4096,
|
||||
vec=src_vec,
|
||||
inclusive=False,
|
||||
nest=False,
|
||||
radius=(annulus_outer * u.arcsecond).to(u.radian).value,
|
||||
)
|
||||
|
||||
|
||||
|
||||
annulus_pixel_list = [
|
||||
item for item in outer_pixel_list if item not in inner_pixel_list
|
||||
]
|
||||
|
||||
|
||||
|
||||
source_pixels = Pixel.objects.filter(
|
||||
hpid__in = source_pixel_list,
|
||||
survey__in = survey_numbers
|
||||
)
|
||||
|
||||
annulus_pixels = Pixel.objects.filter(
|
||||
hpid__in = annulus_pixel_list,
|
||||
survey__in = survey_numbers
|
||||
)
|
||||
|
||||
# check contamination
|
||||
contamination = (
|
||||
source_pixels.filter(contaminated=True).exists() or
|
||||
annulus_pixels.filter(contaminated=True).exists()
|
||||
hpid__in=source_pixel_list, survey__in=survey_numbers
|
||||
)
|
||||
|
||||
annulus_pixels = Pixel.objects.filter(
|
||||
hpid__in=annulus_pixel_list, survey__in=survey_numbers
|
||||
)
|
||||
|
||||
# check contamination
|
||||
contamination = (
|
||||
source_pixels.filter(contaminated=True).exists()
|
||||
or annulus_pixels.filter(contaminated=True).exists()
|
||||
)
|
||||
|
||||
|
||||
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
|
||||
)
|
||||
status=status.HTTP_404_NOT_FOUND,
|
||||
)
|
||||
|
||||
|
||||
|
||||
# COMPUTE COUNTS, BACKGROUND ESTIMATE, EXPOSURE
|
||||
# **************************************************************
|
||||
|
||||
|
||||
N = sum(obj.counts for obj in source_pixels)
|
||||
|
||||
|
||||
Nnpix = len(source_pixels)
|
||||
|
||||
|
||||
Bcounts = sum(obj.counts for obj in annulus_pixels)
|
||||
|
||||
|
||||
Bnpix = len(annulus_pixels)
|
||||
|
||||
|
||||
B = Bcounts / Bnpix * Nnpix
|
||||
|
||||
|
||||
tsum = sum(obj.exposure for obj in source_pixels)
|
||||
|
||||
|
||||
t = tsum / Nnpix
|
||||
|
||||
|
||||
# CONSTANTS
|
||||
# **************************************************************
|
||||
|
||||
#EEF = .9 # eclosed energy fraction, .5 for hpd, .9 for w90
|
||||
#ECF = 4e-11 # energy conversion factor
|
||||
|
||||
EEF = .80091 # use values from the paper
|
||||
|
||||
# EEF = .9 # eclosed energy fraction, .5 for hpd, .9 for w90
|
||||
# ECF = 4e-11 # energy conversion factor
|
||||
|
||||
EEF = 0.80091 # use values from the paper
|
||||
ECF = 3.3423184e-11
|
||||
|
||||
|
||||
# BAYESIAN IMPLEMENTATION VIA POISSON_CONF_INTERVAL
|
||||
# **************************************************************
|
||||
|
||||
|
||||
low, high = poisson_conf_interval(
|
||||
n = N,
|
||||
background = B,
|
||||
interval = 'kraft-burrows-nousek',
|
||||
confidence_level=confidence_level
|
||||
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_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_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_ul = sp.gammainccinv(N + 1, 1 - confidence_level) - B
|
||||
classic_count_ll = sp.gammainccinv(N, confidence_level) - B
|
||||
|
||||
|
||||
if not np.isfinite(classic_count_ll) or classic_count_ll < 0:
|
||||
classic_count_ll = 0.0
|
||||
|
||||
|
||||
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_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 # source count rate
|
||||
|
||||
BR = B / t # background rate within aperture
|
||||
|
||||
FL = CR * ECF # conversion to flux
|
||||
|
||||
Flux = max(FL, 0) # flux cannot be lower than zero
|
||||
|
||||
|
||||
S = N - B # counts as simply counts within aperture
|
||||
# with the background estimate subtracted
|
||||
|
||||
CR = S / t / EEF # source count rate
|
||||
|
||||
BR = B / t # background rate within aperture
|
||||
|
||||
FL = CR * ECF # conversion to flux
|
||||
|
||||
Flux = max(FL, 0) # flux cannot be lower than zero
|
||||
|
||||
# NEARBY SOURCES CHECK
|
||||
# ****************************************************************
|
||||
|
||||
|
||||
radius_as = 120
|
||||
radius_deg = radius_as / 3600
|
||||
|
||||
|
||||
dec_min = max(dec - radius_deg, -90)
|
||||
dec_max = min(dec + radius_deg, 90)
|
||||
|
||||
dec_max = min(dec + radius_deg, 90)
|
||||
|
||||
# cheap belt query
|
||||
belt_sources = CatalogSource.objects.filter(
|
||||
dec_deg__gte = dec_min,
|
||||
dec_deg__lte = dec_max
|
||||
dec_deg__gte=dec_min, dec_deg__lte=dec_max
|
||||
)
|
||||
|
||||
center_coord = SkyCoord(ra, dec, unit='deg')
|
||||
|
||||
|
||||
center_coord = SkyCoord(ra, dec, unit="deg")
|
||||
|
||||
nearby_sources = []
|
||||
|
||||
#refine belt to circular region using astropy separation
|
||||
|
||||
# refine belt to circular region using astropy separation
|
||||
for catsrc in belt_sources:
|
||||
catsrc_coord = SkyCoord(catsrc.ra_deg, catsrc.dec_deg, unit='deg')
|
||||
catsrc_coord = SkyCoord(catsrc.ra_deg, catsrc.dec_deg, unit="deg")
|
||||
if center_coord.separation(catsrc_coord).deg <= radius_deg:
|
||||
nearby_sources.append(
|
||||
{
|
||||
'srcid' : catsrc.srcid,
|
||||
'name' : catsrc.name,
|
||||
'ra_deg' : catsrc.ra_deg,
|
||||
'dec_deg' : catsrc.dec_deg,
|
||||
'pos_error' : catsrc.pos_error,
|
||||
'significance' : catsrc.significance,
|
||||
'flux' : catsrc.flux,
|
||||
'flux_error' : catsrc.flux_error,
|
||||
'catalog_name' : catsrc.catalog_name,
|
||||
'new_xray' : catsrc.new_xray,
|
||||
'source_type' : catsrc.source_type
|
||||
"srcid": catsrc.srcid,
|
||||
"name": catsrc.name,
|
||||
"ra_deg": catsrc.ra_deg,
|
||||
"dec_deg": catsrc.dec_deg,
|
||||
"pos_error": catsrc.pos_error,
|
||||
"significance": catsrc.significance,
|
||||
"flux": catsrc.flux,
|
||||
"flux_error": catsrc.flux_error,
|
||||
"catalog_name": catsrc.catalog_name,
|
||||
"new_xray": catsrc.new_xray,
|
||||
"source_type": catsrc.source_type,
|
||||
}
|
||||
)
|
||||
|
||||
|
||||
# SQUARE REGION IMAGE SERVING
|
||||
# ****************************************************************
|
||||
|
||||
# get hpids within a circle of radius sqrt(2) * outer annulus radius
|
||||
|
||||
# get hpids within a circle of radius sqrt(2) * outer annulus radius
|
||||
map_radius = annulus_outer * np.sqrt(2)
|
||||
|
||||
|
||||
map_pixel_list = hp.query_disc(
|
||||
nside = 4096,
|
||||
vec = src_vec,
|
||||
inclusive = False,
|
||||
nest = False,
|
||||
radius = (map_radius * u.arcsecond).to(u.radian).value
|
||||
nside=4096,
|
||||
vec=src_vec,
|
||||
inclusive=False,
|
||||
nest=False,
|
||||
radius=(map_radius * u.arcsecond).to(u.radian).value,
|
||||
)
|
||||
|
||||
|
||||
# fetch those pixels for the requested surveys
|
||||
# summing counts and sorting by hpid
|
||||
|
||||
|
||||
map_pixels_qs = (
|
||||
Pixel.objects
|
||||
.filter(hpid__in = map_pixel_list, survey__in = survey_numbers)
|
||||
.values('hpid')
|
||||
.annotate(counts=Sum('counts'))
|
||||
.order_by('hpid')
|
||||
Pixel.objects.filter(hpid__in=map_pixel_list, survey__in=survey_numbers)
|
||||
.values("hpid")
|
||||
.annotate(counts=Sum("counts"))
|
||||
.order_by("hpid")
|
||||
)
|
||||
|
||||
|
||||
# turn the queryset to a list
|
||||
map_pixels_list = list(map_pixels_qs)
|
||||
|
||||
|
||||
# get lists of healpix indices and count values
|
||||
map_healpix_list = [d['hpid'] for d in map_pixels_list]
|
||||
map_counts_list = [d['counts'] for d in map_pixels_list]
|
||||
|
||||
map_healpix_list = [d["hpid"] for d in map_pixels_list]
|
||||
map_counts_list = [d["counts"] for d in map_pixels_list]
|
||||
|
||||
# set map nside
|
||||
map_nside = 4096
|
||||
|
||||
|
||||
# set map order
|
||||
map_order = 'ring'
|
||||
|
||||
map_order = "ring"
|
||||
|
||||
# assemble the result dict
|
||||
map_dict = {
|
||||
'healpix' : map_healpix_list,
|
||||
'counts' : map_counts_list,
|
||||
'nside' : map_nside,
|
||||
'order' : map_order,
|
||||
'radius_as' : map_radius
|
||||
"healpix": map_healpix_list,
|
||||
"counts": map_counts_list,
|
||||
"nside": map_nside,
|
||||
"order": map_order,
|
||||
"radius_as": map_radius,
|
||||
}
|
||||
|
||||
|
||||
# RESULT JSON
|
||||
# ****************************************************************
|
||||
|
||||
|
||||
result = {
|
||||
# frequentist limits
|
||||
'ClassicUpperLimit' : classic_count_ul,
|
||||
'ClassicLowerLimit' : classic_count_ll,
|
||||
'ClassicCountRateUpperLimit' : classic_rate_ul,
|
||||
'ClassicCountRateLowerLimit' : classic_rate_ll,
|
||||
'ClassicFluxUpperLimit' : classic_flux_ul,
|
||||
'ClassicFluxLowerLimit' : classic_flux_ll,
|
||||
"ClassicUpperLimit": classic_count_ul,
|
||||
"ClassicLowerLimit": classic_count_ll,
|
||||
"ClassicCountRateUpperLimit": classic_rate_ul,
|
||||
"ClassicCountRateLowerLimit": classic_rate_ll,
|
||||
"ClassicFluxUpperLimit": classic_flux_ul,
|
||||
"ClassicFluxLowerLimit": classic_flux_ll,
|
||||
# bayesian limits
|
||||
'BayesianUpperLimit' : bayesian_count_ul,
|
||||
'BayesianLowerLimit' : bayesian_count_ll,
|
||||
'BayesianCountRateUpperLimit' : bayesian_rate_ul,
|
||||
'BayesianCountRateLowerLimit' : bayesian_rate_ll,
|
||||
'BayesianFluxUpperLimit' : bayesian_flux_ul,
|
||||
'BayesianFluxLowerLimit' : bayesian_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,
|
||||
# flux 'center value' estimate
|
||||
'FluxEstimate' : Flux,
|
||||
"FluxEstimate": Flux,
|
||||
# raw data
|
||||
'ApertureCounts' : N,
|
||||
'ApertureBackgroundCounts' : B,
|
||||
'SourceCounts' : S,
|
||||
'Exposure' : t,
|
||||
"ApertureCounts": N,
|
||||
"ApertureBackgroundCounts": B,
|
||||
"SourceCounts": S,
|
||||
"Exposure": t,
|
||||
# count rates
|
||||
'SourceRate' : CR,
|
||||
'BackgroundRate' : BR,
|
||||
"SourceRate": CR,
|
||||
"BackgroundRate": BR,
|
||||
# contamination
|
||||
'Contamination' : contamination,
|
||||
'NearbySources' : nearby_sources,
|
||||
"Contamination": contamination,
|
||||
"NearbySources": nearby_sources,
|
||||
# count map for the frontend image
|
||||
'CountMap' : map_dict
|
||||
"CountMap": map_dict,
|
||||
}
|
||||
|
||||
clean = sanitize(result) # calling sanitize() to convert NaN to null
|
||||
|
||||
return Response(clean, status=status.HTTP_200_OK)
|
||||
|
||||
clean = sanitize(result) # calling sanitize() to convert NaN to null
|
||||
|
||||
return Response(clean, status=status.HTTP_200_OK)
|
||||
|
||||
Reference in New Issue
Block a user