So I wrote some code a month ago, and I've been consistently running/updating it. I uploaded my most recent one to GitHub and it works I know it works because I tested it over and over again before uploading. However, now I opened up the file nothing changed and submitting queries... NO LONGER WORKS, and by no longer works I mean that out of the 150 queries 2 succeed. I have the data from my most recent script and I know 104/150 work. Anyone know why this might be? My code is below
"""
Imports needed for the code.
"""
"""
Script to get and clean data
"""
import numpy as np
import pandas as pd
from itertools import chain
from astroquery.gaia import Gaia
from pynverse import inversefunc
from astropy.io import ascii
import wget
import requests
import matplotlib.pyplot as plt
import numpy as np
import math
import pandas as pd
from sklearn.metrics import r2_score
from scipy import stats
import sklearn.metrics as sm
defaults = [0] * 3#needed for ignoring values that don't exsist
data = []#array for storing data
def reject_outliers(data):#Outlier Rejection Function
m = 2
u = np.mean(data)
s = np.std(data)
filtered = [e for e in data if (u - 2 * s < e < u + 2 * s)]
return filtered
def isNaN(num):#Checking if it is NaN(Not a Number)
return num != num
def HMS2deg(ra='', dec=''):#Convert from form RA to Degree RA(Gaia Form)
RA, DEC, rs, ds = '', '', 1, 1
if ra:
H, M, S, *_ = [float(i) for i in chain(ra.split(), defaults)]
if str(H)[0] == '-':
rs, H = -1, abs(H)
deg = (H*15) + (M/4)
RA = '{0}'.format(deg*rs)
if ra and dec:
return (RA, DEC)
else:
return RA or DEC
def HMS2degDEC(dec='', ra=''):#Convert from form Dec to Degree Dec(Gaia Form)
RA, DEC, rs, ds = '', '', 1, 1
if dec:
D, M, S, *_ = [float(i) for i in chain(dec.split(), defaults)]
S = S[0] if S else 0
if str(D)[0] == '-':
ds, D = -1, abs(D)
deg = D + (M/60) + (S/3600)
DEC = '{0}'.format(deg*ds)
if ra and dec:
return (RA, DEC)
else:
return RA or DEC
count=1
csv_file='test1.csv'#Data Storing File for Gaia
data = pd.read_csv(csv_file, error_bad_lines=False)#Ignore the bad lines
radata=data['R.A.']#get RA
decdata=data['Dec.']#get dec
agedata=data['Age(Myr)']#get Age
diamaterdata=data['Diameter']#get Diameter later converted to FOV
ra=[]#cleaned RA
dec=[]#cleaned Dec
age=[]#Cleaned age
csv_files=['M42.csv', 'Horsehead.csv', 'M93.csv', 'IrisTrain.csv']#Pre exsisting data
ages=[3, 6, 25, 0.055]#pre exsisting data's age
diameter=[]#Diameter cleaned data
gooddata=[]#Overall data storage for cleaned data
for i in range(len(radata)):#cleaning RA data and converting
if(isNaN(radata[i])):
ra.append(0)
else:
ra.append(HMS2deg(radata[i]))
print(ra)
for i in range(len(decdata)):#Cleaning Dec Data and converting
if(isNaN(decdata[i])):
dec.append(0)
else:
dec.append(HMS2degDEC(decdata[i]))
print(dec)
for i in range(len(diamaterdata)):#cleaning diameter data and converting to FOV
if(isNaN(diamaterdata[i])):
diameter.append(0)
else:
diameter.append(((diamaterdata[i])/3600)*100)
print(diameter)
for i in range(len(ra)):#Modified Query for each object
query1=""" SELECT bp_rp, parallax, pmra, pmdec, phot_g_mean_mag AS gp
FROM gaiadr2.gaia_source
WHERE 1 = CONTAINS(POINT('ICRS', ra, dec),
"""
query1=query1+" CIRCLE('ICRS'," +str(ra[i])+","+ str(dec[i])+","+str(diameter[i])+")"+")"
string2="""
AND phot_g_mean_flux_over_error > 50
AND phot_rp_mean_flux_over_error > 20
AND phot_bp_mean_flux_over_error > 20
AND visibility_periods_used > 8
"""
print(query1)
query1=query1+string2
try:#Try the following code
job = Gaia.launch_job(query1)#Launch query to gaia webpage
print(job)
results = job.get_results()#get results
ascii.write(results, 'values'+str(count)+'.csv', format='csv', fast_writer=False)
csv_files.append('values'+str(count)+'.csv')#store in CSV
ages.append(agedata[i])#append data
print(ages)
count+=1#avoid re-writing CSV file by creating different ones
except:#If the code throws any error, usually 'can't query' it will ignore the file, another filter to clean out any useless or bad data
continue
"""
End of Cleaning and Gathering Data
"""
"""
Training and Creating Model with the data
"""
arr2=[]
datasetY=[]
datasetX=[]
Y=[]
av=0
count=[]
count2=[]
MAD=[]
"""
def adjR(x, y, degree):
results = {}
coeffs = np.polyfit(x, y, degree)
p = np.poly1d(coeffs)
yhat = p(x)
ybar = np.sum(y)/len(y)
ssreg = np.sum((yhat-ybar)**2)
sstot = np.sum((y - ybar)**2)
results['r_squared'] = 1- (((1-(ssreg/sstot))*(len(y)-1))/(len(y)-degree-1)
return results
original accuracy calculation
"""
"""
def objective(x, a, b, c):
return a * x + b
needed for scipy modeling, polyfit was more accurate
"""
"""
Line 59-68 checks if CSV data is NAN if it is it will ignore the value and only take the data that can be used
"""
count=0
for i in range(len(csv_files)):
data=pd.read_csv(csv_files[i])
arr=data['gp']
arr2=data['bp_rp']
for i in range(len(arr2)):
if(isNaN(arr2[i])):
continue
elif(13<=arr[i]<=19):
datasetX.append(arr2[i])
datasetY.append(arr[i])
count+=1
mad=stats.median_absolute_deviation(datasetY)#Calculate MAD for Magnitude
mad2=stats.median_absolute_deviation(datasetX)#Calculate MAD for Color
madav=(mad+mad2)/2#Total MAD
MAD.append(count)#Appending to an Array for training and plotting
datasetX.clear()#Clearing for next Iteration
datasetY.clear()#Clearing for next Iteration
count=0
"""
Plotting data and Traning
"""
ages3=[]
MAD2=[]
ages2 = [4000 if math.isnan(i) else i for i in ages]#ignore any age nan values
print(len(ages3))
print(len(MAD))
MAD=[1.5 if math.isnan(i) else i for i in MAD]#ignore any MAD computation error values
for i in range(len(MAD)):
if(-500<=MAD[i]<=1500 and -25<=ages2[i]<170 or (100<=MAD[i]<=1262) and (278<=ages2[i]<=5067) or (-20<=MAD[i]<=20) and (3900<=ages2[i]<=4100) or (2642<=MAD[i]<=4750) and (0<=ages2[i]<=200) or (7800<=MAD[i]<=315800) and (0<=ages2[i]<=20)):
continue
else:
ages3.append(float(ages2[i]))
MAD2.append(float(MAD[i]))
fig = plt.figure()
ax1 = fig.add_subplot('111')
ax1.scatter(ages3, MAD2, color='blue')
plt.ylim(-7800,315800)
polyline = np.linspace(-5, 9000, 20)
mod1 = np.poly1d(np.polyfit(ages3, MAD2, 2))#Train for a function of degree 2
predict = np.poly1d(mod1)
ax1.plot(polyline,mod1(polyline), color='red')
print(np.interp(0.795, mod1(polyline),polyline))
print(mod1)#print model
plt.show()
"""
End of Training and Creating model/End of Script
"""
Please focus on this part, the querying section:
for i in range(len(ra)):#Modified Query for each object
query1=""" SELECT bp_rp, parallax, pmra, pmdec, phot_g_mean_mag AS gp
FROM gaiadr2.gaia_source
WHERE 1 = CONTAINS(POINT('ICRS', ra, dec),
"""
query1=query1+" CIRCLE('ICRS'," +str(ra[i])+","+ str(dec[i])+","+str(diameter[i])+")"+")"
string2="""
AND phot_g_mean_flux_over_error > 50
AND phot_rp_mean_flux_over_error > 20
AND phot_bp_mean_flux_over_error > 20
AND visibility_periods_used > 8
"""
print(query1)
query1=query1+string2
try:#Try the following code
job = Gaia.launch_job(query1)#Launch query to gaia webpage
print(job)
results = job.get_results()#get results
ascii.write(results, 'values'+str(count)+'.csv', format='csv', fast_writer=False)
csv_files.append('values'+str(count)+'.csv')#store in CSV
ages.append(agedata[i])#append data
print(ages)
count+=1#avoid re-writing CSV file by creating different ones
except:#If the code throws any error, usually 'can't query' it will ignore the file, another filter to clean out any useless or bad data
continue
Thank you for your time. I know this is really unusual. After removing the try/except this is the errors:
Traceback (most recent call last):
File "read.py", line 120, in <module>
job = Gaia.launch_job(query1)#Launch query to gaia webpage
File "C:\ProgramData\Anaconda3\lib\site-packages\astroquery\gaia\core.py", line 846, in launch_job
return TapPlus.launch_job(self, query=query, name=name,
File "C:\ProgramData\Anaconda3\lib\site-packages\astroquery\utils\tap\core.py", line 344, in launch_job
results = utils.read_http_response(response, output_format)
File "C:\ProgramData\Anaconda3\lib\site-packages\astroquery\utils\tap\xmlparser\utils.py", line 42, in read_http_response
result = APTable.read(data, format=astropyFormat)
File "C:\ProgramData\Anaconda3\lib\site-packages\astropy\table\connect.py", line 61, in __call__
out = registry.read(cls, *args, **kwargs)
File "C:\ProgramData\Anaconda3\lib\site-packages\astropy\io\registry.py", line 520, in read
data = reader(*args, **kwargs)
File "C:\ProgramData\Anaconda3\lib\site-packages\astropy\io\votable\connect.py", line 116, in read_table_votable
raise ValueError("No table found")
ValueError: No table found
Please note, this has been resolved. The reason for this is on their website: https://www.cosmos.esa.int/web/gaia/news, planned maintenance. For future reference, if your code stops working and it involves Querying, head to their website they have probably posted it.