def retrieve_ESO_files(rawpath='/Volumes/passport/w51-apex/raw/',
username='******', projids=['098.C-0421',],
download=False):
# don't touch the rest
Eso.cache_location = rawpath
Eso.login(username)
Eso.ROW_LIMIT = 1000000
#tbl = Eso.query_instrument('apex', pi_coi='ginsburg', cache=False)
#stbl = tbl[np.char.startswith(tbl['Object'], 'Map') & (tbl['Scan Mode']=='OTF') & (tbl['Number of subscans'] > 10)]
#programs = set(tbl['ProgId'])
#projids = set(tbl['APEX Project ID'])
all_files = []
for proj in projids:
tbl = Eso.query_apex_quicklooks(proj, cache=False)
print(tbl)
if download:
files = Eso.retrieve_data(tbl['Product ID'])
all_files.append(files)
return all_files
def retrieve_ESO_files(rawpath='/Volumes/passport/w51-apex/raw/',
username='******',
projids=[
'098.C-0421',
],
download=False):
# don't touch the rest
Eso.cache_location = rawpath
Eso.login(username)
Eso.ROW_LIMIT = 1000000
#tbl = Eso.query_instrument('apex', pi_coi='ginsburg', cache=False)
#stbl = tbl[np.char.startswith(tbl['Object'], 'Map') & (tbl['Scan Mode']=='OTF') & (tbl['Number of subscans'] > 10)]
#programs = set(tbl['ProgId'])
#projids = set(tbl['APEX Project ID'])
all_files = []
for proj in projids:
tbl = Eso.query_apex_quicklooks(proj, cache=False)
print(tbl)
if download:
files = Eso.retrieve_data(tbl['Product ID'], continuation=True)
all_files.append(files)
return all_files
def retrieve_ESO_files(rawpath='/scratch/aginsbur/apex/raw/',
username='******', projids=['O-085.F-9311A',
'E-085.B-0964A',
'E-093.C-0144A',
'E-095.C-0242A']):
# don't touch the rest
Eso.cache_location = rawpath
Eso.login(username)
Eso.ROW_LIMIT = 1000000
#tbl = Eso.query_instrument('apex', pi_coi='ginsburg', cache=False)
#stbl = tbl[np.char.startswith(tbl['Object'], 'Map') & (tbl['Scan Mode']=='OTF') & (tbl['Number of subscans'] > 10)]
#programs = set(tbl['ProgId'])
#projids = set(tbl['APEX Project ID'])
for proj in projids:
tbl = Eso.query_apex_quicklooks(proj)
print(tbl)
def retrieve_ESO_files(rawpath='/scratch/aginsbur/apex/raw/',
username='******',
projids=[
'O-085.F-9311A', 'E-085.B-0964A', 'E-093.C-0144A',
'E-095.C-0242A'
]):
# don't touch the rest
Eso.cache_location = rawpath
Eso.login(username)
Eso.ROW_LIMIT = 1000000
#tbl = Eso.query_instrument('apex', pi_coi='ginsburg', cache=False)
#stbl = tbl[np.char.startswith(tbl['Object'], 'Map') & (tbl['Scan Mode']=='OTF') & (tbl['Number of subscans'] > 10)]
#programs = set(tbl['ProgId'])
#projids = set(tbl['APEX Project ID'])
for proj in projids:
tbl = Eso.query_apex_quicklooks(proj)
print(tbl)
from astroquery.eso import Eso
import shutil
# log in so you can get proprietary data
Eso.login('aginsburg')
# make sure you don't filter out anything
Eso.ROW_LIMIT = 1e6
# List all of your pi/co projects
all_pi_proj = Eso.query_instrument('apex', pi_coi='ginsburg')
# Have a look at the project IDs only
print(set(all_pi_proj['APEX Project ID']))
# set(['E-095.F-9802A-2015', 'E-095.C-0242A-2015', 'E-093.C-0144A-2014'])
# The full project name includes prefix and suffix
full_proj = 'E-095.F-9802A-2015'
proj_id = full_proj[2:-6]
# Then get the APEX quicklook "reduced" data
tbl = Eso.query_apex_quicklooks(prog_id=proj_id)
# and finally, download it
files = Eso.retrieve_data(tbl['Product ID'])
# then move the files to your local directory
for fn in files:
shutil.move(fn, '.')
import logging
import pg
import re
import time
import yaml
from astropy.extern.six import BytesIO, cPickle as pickle
from astropy.table import Table
from astroquery.eso import Eso as ESO
from astroquery.eso.core import _check_response
# Load local catalog of positions.
local_catalog = Table.read("data/HARPS_all.csv")
# Login to ESO.
eso = ESO()
eso.login("andycasey")
eso.ROW_LIMIT = 100000 # Maximum possible number of observations per star
# Connect to the PostgreSQL database.
cwd = os.path.dirname(os.path.realpath(__file__))
with open(os.path.join(cwd, "../db/credentials.yaml"), "r") as fp:
credentials = yaml.load(fp)
connection = pg.connect(**credentials)
def query_harps_phase3_by_position(ra, dec, **kwargs):
"""
Query the ESO Phase 3 science archive by position.
:param ra:
Right ascension [degrees].
def login(user):
eso = Eso()
eso.login(user, store_password=True)
return eso
print("In total we will request {} records in {} requests".format(N, I))
for i in range(I):
if i < SKIP:
print("Skipping {}".format(i + 1))
continue
print("Starting with batch number {}/{}".format(i + 1, I))
data = [("dataset", dataset)
for dataset in records[i * BATCH:(i + 1) * BATCH]]
# Login to ESO.
eso = ESO()
eso.login(ESO_USERNAME)
prepare_response = eso._session.request(
"POST", "http://dataportal.eso.org/rh/confirmation", data=data)
assert prepare_response.ok
# Additional payload items required for confirmation.
data += [
("requestDescription", ""),
("deliveryMediaType",
"WEB"), # OR USB_DISK --> Holy shit what the f**k!
("requestCommand", "SELECTIVE_HOTFLY"),
("submit", "Submit")
]
confirmation_response = eso._session.request(
"2013-01-23",
"2013-01-26",
"2013-01-30",
"2013-02-01",
"2013-02-06",
"2013-02-07",
"2013-02-08",
"2013-02-11",
"2013-02-13",
]
destination = join(dirname(__file__), "raw")
print(destination)
dates = [dt.datetime.strptime(d, "%Y-%m-%d") for d in dates]
day = dt.timedelta(days=1)
eso = Eso()
eso.login("awehrhahn")
for d in dates:
filters = {
"instrument": instrument,
"dp_cat": "CALIB",
"stime": str(d - day)[:10],
"etime": str(d + day)[:10],
}
table = eso.query_main(column_filters=filters)
files = table["Dataset ID"]
eso.retrieve_data(files, destination=destination, continuation=True)
def grab_calfiles():
workingdir = os.getcwd()
handler = Eso()
### Set your username here!
USERNAME = ""
handler.ROW_LIMIT = 10000
handler.login(USERNAME, store_password=True)
def mkdir_safe(dirname):
'''
Check if directory exists - if it doesn't, make it, if it does, clear it out
'''
if os.path.isdir(dirname) == True:
flist = glob.glob(dirname + "/*")
for f in flist:
os.remove(f)
else:
os.mkdir(dirname)
mkdir_safe("flats")
mkdir_safe("flatdarks")
mkdir_safe("darks")
# Read the first FITS in the folder
filelist = glob.glob("obj/*.fits")
print(os.getcwd())
temphdu = fits.open(filelist[0])
header = temphdu[0].header
print("FITS header loaded")
# Extract relevant query params from science frame
prop_ID = header["HIERARCH ESO OBS PROG ID"]
date = Time(header["DATE-OBS"])
sci_exp = header["EXPTIME"]
# Set start and end time of search - may need to tweak this manually to find the right calfiles.
# Best to be generous with this window since need to find flats, darks, and flat-darks for the pipeline to run.
stime = date
etime = date + 18 * u.hour
win_size = header["HIERARCH ESO DET WINDOW NY"]
sci_wav = header["HIERARCH ESO INS WLEN CWLEN"]
#print(filelist[0], sci_wav, date)
# Query flat frames - check they match
print("Querying ESO Archive")
flat_table = handler.query_instrument("crires",
column_filters={
'stime': stime.value,
'etime': etime.value,
'dp_type': 'FLAT',
'ins_wlen_cwlen': sci_wav
})
flat_header = handler.get_headers(flat_table["DP.ID"])
mask = flat_header["HIERARCH ESO DET WINDOW NY"] != win_size
flat_table = flat_table[~mask]
#### if flat_exp_time not all the same value, choose the highest one
#### Download flat fields
flat_exp_time = np.max(flat_table["EXPTIME"])
flat_files = handler.retrieve_data(flat_table["DP.ID"])
#print(flat_files)
for f in flat_files:
shutil.copy(f, "flats")
#### Grab the dark frames matching the science exposure time
dark_table = handler.query_instrument("crires",
column_filters={
'stime': stime.value,
'etime': etime.value,
'dp_type': 'DARK',
'exptime': sci_exp
})
dark_header = handler.get_headers(dark_table['DP.ID'])
mask = dark_header["HIERARCH ESO DET WINDOW NY"] != win_size
dark_table = dark_table[~mask]
dark_files = handler.retrieve_data(dark_table["DP.ID"])
for d in dark_files:
shutil.copy(d, "darks")
#### Grab darks matched to flat fields
flatdark_table = handler.query_instrument("crires",
column_filters={
'stime': stime.value,
'etime': etime.value,
'dp_type': 'DARK',
'exptime': flat_exp_time
})
flatdark_header = handler.get_headers(flatdark_table["DP.ID"])
mask = flatdark_header["HIERARCH ESO DET WINDOW NY"] != win_size
flatdark_table = flatdark_table[~mask]
flatdark_files = handler.retrieve_data(flatdark_table["DP.ID"])
for d in flatdark_files:
shutil.copy(d, "flatdarks")
print("Unpacking and moving!")
### Unpack all the files -- several possible commands for thisself.
### maximum compatibility use "gzip -d *.Z"
### pigz is a parallel gzip, but also it can't decompress in parallel apparently.
### if you want to use it despite this, "pigz -d *.Z"
### For maximum SPEED you could try "ls *.Z | parallel pigz -d" if you have GNU parallel installed.
os.chdir("flats")
os.system("pigz -d *.Z")
os.chdir("../flatdarks")
os.system("pigz -d *.Z")
os.chdir("../darks")
os.system("pigz -d *.Z")
os.chdir("../")
print("Calibration selection complete!")
typemask = [spectral_type_cut(x) for x in spectype]
varmask = [not x for x in varstat]
### Needs to be both not variable and not a GKM/whatever else star
totalmask = np.logical_and(typemask, varmask)
new_subset = cat_subset[totalmask]
print("Filter by spectral_type: %s of %s targets remain" %
(np.sum(typemask), len(initmask)))
science_frames = new_subset["DP.ID"]
eso = Eso()
eso.login("tkillestein")
### Mask all that have non-512 window
heads = eso.get_headers(science_frames)
goodmsk = heads['HIERARCH ESO DET WINDOW NY'] == 512
print("Filter by windowing: %s of %s targets remain" %
(np.sum(goodmsk), len(initmask)))
check_calib_list = heads[goodmsk]
final_frames = []
frames_rejected = 0
for head in tqdm(check_calib_list,
ascii=True,
class ESOquery():
"""
ESO query class
Parameters
----------
user: str
User name used in ESO website
Returns
-------
"""
def __init__(self, user):
self.user = user
self.eso = Eso()
self.eso.login(self.user) #login in eso
self.eso.ROW_LIMIT = -1 #unlimited number of search results
self.instruments = np.array(['FEROS', 'UVES', 'HARPS', 'ESPRESSO'])
def searchReleaseDate(self, star):
"""
Searches the date the data was released
Parameters
----------
star: str
Name of the star
Returns
-------
result: array
Array with the date of the data release
"""
search = self.eso.query_main(column_filters={'target': star})
result = np.array(search['Release_Date'])
return result
def searchObservationDate(self, star):
"""
Searches for the modified Julian Date (JD - 2400000.5) of the start of
the observation
Parameters
----------
star: str
Name of the star
Returns
-------
result: array
Array with the start date of the observations
"""
search = self.eso.query_main(column_filters={'target': star})
result = np.array(search['MJD-OBS'])
return result
def searchInstruments(self, star):
"""
Checks which instruments where used for the given star and how many
observations it made
Parameters
----------
star: str
Name of the star
Returns
-------
instrumentDict: dict
Instruments and number of observations
"""
searchResult = self.eso.query_main(column_filters={'target': star})
instruments = np.unique(np.array(searchResult['Instrument']),
return_counts=True)
instrumentDict = dict()
for i, j in enumerate(instruments[0]):
instrumentDict[j] = instruments[1][i]
return instrumentDict
def _searchAndDownload(self, star, instrument, downloadPath, date, calib):
"""
Download ESO spectra of a given star; to be used is getStarData()
Parameters
----------
star: str
Name of the star
instrument: str
Instrument we are searching the data
date: float
Download spectra younger than date (in modified Julian Date)
calib : str
Retrieve associated calibration files: 'none' (default), 'raw' for
raw calibrations, or 'processed' for processed calibrations.
Returns
-------
"""
print('Downloading {0} data\n'.format(instrument))
table = self.eso.query_main(column_filters={
'instrument': instrument,
'target': star
})
if downloadPath:
self.eso.retrieve_data(table['Dataset ID'],
destination=downloadPath,
with_calib=calib)
return 0
else:
self.eso.retrieve_data(table['Dataset ID'], with_calib=calib)
return 0
def getALLdata(self, star, downloadPath=None, date=None, calib='none'):
"""
Download ESO spectra of a given star
Parameters
----------
star: str
Name of the star
downloadPatch: str
Adress where to download data
date: str
Download only the data past a certain date
calib : str
Retrieve associated calibration files: 'None' (default), 'raw' for
raw calibrations, or 'processed' for processed calibrations.
Returns
-------
"""
checkInstruments = self.searchInstruments(star)
for _, j in enumerate(self.instruments):
print('\n*** Searching for {0} results ***\n'.format(j))
if j in checkInstruments:
self._searchAndDownload(star, j, downloadPath, date, calib)
else:
print('No {0} data\n'.format(j))
print('\n*** Done ***\n')
return 0
def getFEROSdata(self, star, downloadPath=None, date=None, calib='none'):
"""
Download FEROS spectra of a given star
Parameters
----------
star: str
Name of the star
downloadPatch: str
Adress where to download data
date: float
Download spectra younger than date (in modified Julian Date)
calib : str
Retrieve associated calibration files: 'None' (default), 'raw' for
raw calibrations, or 'processed' for processed calibrations.
Returns
-------
"""
checkInstruments = self.searchInstruments(star)
esoInst = np.array(['FEROS'])
for _, j in enumerate(esoInst):
print('\n*** Searching for {0} results ***\n'.format(j))
if j in checkInstruments:
self._searchAndDownload(star, j, downloadPath, date, calib)
else:
print('No {0} data\n'.format(j))
print('\n*** Done ***\n')
return 0
def getUVESdata(self, star, downloadPath=None, date=None, calib='none'):
"""
Download UVES spectra of a given star
Parameters
----------
star: str
Name of the star
downloadPatch: str
Adress where to download data
date: str
Download only the data past a certain date
calib : str
Retrieve associated calibration files: 'None' (default), 'raw' for
raw calibrations, or 'processed' for processed calibrations.
Returns
-------
"""
checkInstruments = self.searchInstruments(star)
esoInst = np.array(['UVES'])
for _, j in enumerate(esoInst):
print('\n*** Searching for {0} results ***\n'.format(j))
if j in checkInstruments:
self._searchAndDownload(star, j, downloadPath, date, calib)
else:
print('No {0} data\n'.format(j))
print('\n*** Done ***\n')
return 0
def getHARPSdata(self, star, downloadPath=None, date=None, calib='none'):
"""
Download HARPS spectra of a given star
Parameters
----------
star: str
Name of the star
downloadPatch: str
Adress where to download data
date: str
Download only the data past a certain date
calib : str
Retrieve associated calibration files: 'None' (default), 'raw' for
raw calibrations, or 'processed' for processed calibrations.
Returns
-------
"""
checkInstruments = self.searchInstruments(star)
esoInst = np.array(['HARPS'])
for _, j in enumerate(esoInst):
print('\n*** Searching for {0} results ***\n'.format(j))
if j in checkInstruments:
self._searchAndDownload(star, j, downloadPath, date, calib)
else:
print('No {0} data\n'.format(j))
print('\n*** Done ***\n')
return 0
def getESPRESSOdata(self,
star,
downloadPath=None,
date=None,
calib='none'):
"""
Download ESPRESSO spectra of a given star
Parameters
----------
star: str
Name of the star
downloadPath: str
Adress where to download data
date: str
Download only the data past a certain date
calib : str
Retrieve associated calibration files: 'None' (default), 'raw' for
raw calibrations, or 'processed' for processed calibrations.
Returns
-------
"""
checkInstruments = self.searchInstruments(star)
esoInst = np.array(['ESPRESSO'])
for _, j in enumerate(esoInst):
print('\n*** Searching for {0} results ***\n'.format(j))
if j in checkInstruments:
self._searchAndDownload(star, j, downloadPath, date, calib)
else:
print('No {0} data\n'.format(j))
print('\n*** Done ***\n')
return 0
