converted the test script to .py format
This commit is contained in:
@@ -1,170 +0,0 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "4cffd6c5",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"RA List: [np.float64(24.1741435187182), np.float64(25.759787769012984), np.float64(49.32806570275772), np.float64(55.50613654382996), np.float64(60.97590646798826), np.float64(63.018113741788355), np.float64(143.0416839498853), np.float64(161.69014062163393), np.float64(176.53216723085026), np.float64(183.45178780664702), np.float64(191.28607761407375), np.float64(194.20387680952962), np.float64(204.38304472867193), np.float64(339.2669893687885), np.float64(0.8130105246497964), np.float64(164.03825008738184)]\n",
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"Dec List: [np.float64(15.783869592105441), np.float64(13.645005280982105), np.float64(-41.10817408896737), np.float64(-47.22221653992977), np.float64(-43.34878852480052), np.float64(-32.87392378612486), np.float64(21.501827494459036), np.float64(11.819887017791151), np.float64(47.49512808371984), np.float64(14.900261322222237), np.float64(-0.4622668171007003), np.float64(-8.524938659400307), np.float64(8.885499320910338), np.float64(34.4157929700228), np.float64(16.14532447253357), np.float64(6.1729868291531)]\n"
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]
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}
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],
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"source": [
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"import csv\n",
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"from astropy.coordinates import SkyCoord\n",
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"import astropy.units as u\n",
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"\n",
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"# Initialize empty lists for RA and Dec\n",
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"ra_list = []\n",
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"dec_list = []\n",
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"\n",
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"# Define the path to your CSV file\n",
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"csv_file_path = \"GeVgal.csv\"\n",
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"\n",
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"# Open and read the CSV file\n",
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"with open(csv_file_path, 'r') as csvfile:\n",
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" # Use csv.reader to handle the file, skipping the header row\n",
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" csv_reader = csv.reader(csvfile)\n",
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" next(csv_reader) # Skip the header row\n",
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"\n",
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" # Loop through each row in the CSV\n",
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" for row in csv_reader:\n",
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" try:\n",
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" # Extract l and b, which are in the second and third columns (index 1 and 2)\n",
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" l = float(row[1])\n",
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" b = float(row[2])\n",
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"\n",
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" # Create a SkyCoord object with galactic coordinates\n",
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" galactic_coord = SkyCoord(l=l*u.degree, b=b*u.degree, frame='galactic')\n",
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"\n",
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" # Convert to ICRS (equatorial) coordinates\n",
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" icrs_coord = galactic_coord.icrs\n",
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"\n",
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" # Append the RA and Dec values to the lists\n",
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" ra_list.append(icrs_coord.ra.deg)\n",
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" dec_list.append(icrs_coord.dec.deg)\n",
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"\n",
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" except (ValueError, IndexError) as e:\n",
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" # Handle potential errors if a row is malformed\n",
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" print(f\"Skipping a malformed row: {row} - Error: {e}\")\n",
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"\n",
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"# Now, ra_list and dec_list contain the converted coordinates\n",
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"print(\"RA List:\", ra_list)\n",
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"print(\"Dec List:\", dec_list)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "ff1d339a",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Request successful!\n",
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"{\n",
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" \"Status\": 0,\n",
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" \"ErrorMessage\": \"\",\n",
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" \"ClassicUpperLimit\": 36.99647944311798,\n",
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" \"ClassicLowerLimit\": 0.0,\n",
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" \"ClassicOneSideUL\": 33.54440898622437,\n",
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" \"ClassicCountRateUpperLimit\": 0.022452965897451615,\n",
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" \"ClassicCountRateLowerLimit\": 0.0,\n",
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" \"ClassicCountRateOneSideUL\": 0.020357922763323065,\n",
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" \"ClassicFluxUpperLimit\": 7.504496105362505e-13,\n",
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" \"ClassicFluxLowerLimit\": 0.0,\n",
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" \"ClassicFluxOneSideUL\": 6.804265983763352e-13,\n",
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" \"BayesianUpperLimit\": 33.83295926177776,\n",
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" \"BayesianLowerLimit\": 0.10792639479099073,\n",
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" \"BayesianOneSideUL\": 33.727107645421896,\n",
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" \"BayesianCountRateUpperLimit\": 0.020533042385357955,\n",
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" \"BayesianCountRateLowerLimit\": 6.549995291856849e-05,\n",
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" \"BayesianCountRateOneSideUL\": 0.020468801604397097,\n",
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" \"BayesianFluxUpperLimit\": 6.862796537256179e-13,\n",
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" \"BayesianFluxLowerLimit\": 2.189216978388652e-15,\n",
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" \"BayesianFluxOneSideUL\": 6.841325222832595e-13,\n",
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" \"FluxEstimate\": 3.2382519031831067e-13,\n",
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" \"ApertureCounts\": 94,\n",
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" \"ApertureBackgroundCounts\": 78.03571428571428,\n",
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" \"SourceCounts\": 15.964285714285722,\n",
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" \"Exposure\": 2057.325295693534,\n",
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" \"SourceRate\": 0.009688639787230046,\n",
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" \"BackgroundRate\": 0.03793066388142964,\n",
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" \"NormalizedBackgroundRate\": 1.6914547063541448e-05,\n",
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" \"Contamination\": false,\n",
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" \"CountMap\": {\n",
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" \"healpix\": [],\n",
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" \"counts\": [],\n",
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" \"exposure\": [],\n",
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" \"nside\": 4096,\n",
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" \"order\": \"ring\",\n",
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" \"radius_as\": 0.0\n",
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" }\n",
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"}\n"
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]
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}
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],
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"source": [
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"import requests\n",
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"import json\n",
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"\n",
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"# Define the URL of your Django API endpoint\n",
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"url = \"http://localhost:8000/api/stacked-upper-limit/\"\n",
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"\n",
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"payload = {\n",
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" \"ra\": ra_list, # List of RA values\n",
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" \"dec\": dec_list, # List of Dec values\n",
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" \"cl\": 0.95, # A numeric confidence level\n",
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" \"survey\": \"1-4\", # A string for the survey parameter\n",
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" \"mr\": 0 # A numeric value for map_radius\n",
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"}\n",
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"\n",
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"try:\n",
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" # Send the PUT request with the JSON payload\n",
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" response = requests.put(url, json=payload)\n",
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"\n",
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" # Check the response status code\n",
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" response.raise_for_status() # This will raise an HTTPError for bad responses (4xx or 5xx)\n",
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"\n",
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" # Print the JSON response from the server\n",
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" print(\"Request successful!\")\n",
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" print(json.dumps(response.json(), indent=4))\n",
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"\n",
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"except requests.exceptions.HTTPError as err:\n",
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" print(f\"HTTP Error: {err}\")\n",
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" print(f\"Response body: {err.response.text}\")\n",
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"except requests.exceptions.RequestException as err:\n",
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" print(f\"An error occurred: {err}\")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": ".venv-pypy",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.11"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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83
stack_request_test.py
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83
stack_request_test.py
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#!/usr/bin/env python
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# coding: utf-8
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# In[1]:
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import csv
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from astropy.coordinates import SkyCoord
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import astropy.units as u
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# Initialize empty lists for RA and Dec
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ra_list = []
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dec_list = []
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# Define the path to your CSV file
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csv_file_path = "GeVgal.csv"
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# Open and read the CSV file
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with open(csv_file_path, 'r') as csvfile:
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# Use csv.reader to handle the file, skipping the header row
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csv_reader = csv.reader(csvfile)
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next(csv_reader) # Skip the header row
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# Loop through each row in the CSV
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for row in csv_reader:
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try:
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# Extract l and b, which are in the second and third columns (index 1 and 2)
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l = float(row[1])
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b = float(row[2])
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# Create a SkyCoord object with galactic coordinates
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galactic_coord = SkyCoord(l=l*u.degree, b=b*u.degree, frame='galactic')
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# Convert to ICRS (equatorial) coordinates
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icrs_coord = galactic_coord.icrs
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# Append the RA and Dec values to the lists
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ra_list.append(icrs_coord.ra.deg)
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dec_list.append(icrs_coord.dec.deg)
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except (ValueError, IndexError) as e:
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# Handle potential errors if a row is malformed
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print(f"Skipping a malformed row: {row} - Error: {e}")
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# Now, ra_list and dec_list contain the converted coordinates
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print("RA List:", ra_list)
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print("Dec List:", dec_list)
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# In[ ]:
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import requests
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import json
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# Define the URL of your Django API endpoint
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url = "http://localhost:8000/api/stacked-upper-limit/"
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payload = {
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"ra": ra_list, # List of RA values
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"dec": dec_list, # List of Dec values
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"cl": 0.95, # A numeric confidence level
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"survey": "1-4", # A string for the survey parameter
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"mr": 0 # A numeric value for map_radius
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}
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try:
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# Send the PUT request with the JSON payload
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response = requests.put(url, json=payload)
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# Check the response status code
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response.raise_for_status() # This will raise an HTTPError for bad responses (4xx or 5xx)
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# Print the JSON response from the server
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print("Request successful!")
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print(json.dumps(response.json(), indent=4))
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except requests.exceptions.HTTPError as err:
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print(f"HTTP Error: {err}")
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print(f"Response body: {err.response.text}")
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except requests.exceptions.RequestException as err:
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print(f"An error occurred: {err}")
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Reference in New Issue
Block a user