def take_fringe(reck_heaters, heater_index, min_voltage, max_voltage, N,
int_time, metadata):
global output_file
output_file = ctx(
'C:/Users/Qubit/Code/lab_code/Calibration/Calibration/data/',
metadata=metadata)
output_file_name = output_file.filename
parameter_space = np.linspace(min_voltage, max_voltage, N)
# Connect to the counting gear and configure it
counter = coincidence_counter(callback=handle_data)
counter.set_integration_time(int_time)
for index, parameter in enumerate(parameter_space):
print 'Setting voltage %s' % str(parameter)
reck_heaters.send_one_voltage(heater_index, parameter)
current_context = reck_heaters.dict()
counter.count(context=current_context)
# Collect and log the last piece of data from the postprocessor
counter.collect()
# Close connections to hardware
counter.kill()
return output_file_name
def parse(datafilename, patterns):
# This loads the CTX file
#dir = os.path.dirname(os.path.realpath(__file__))
#datafilename = os.path.join(dir, '2014_05_13_tuesday_11h57m00s.ctx')
ctxfile=ctx(datafilename)
#print ctxfile
# This pulls out all the stuff to do with count rates
all_counts = list(ctxfile.stream('count_rates'))
# This filters for the count rates we care about
select_counts = lambda data: [parse_coincidence_pattern(pattern, data) for pattern in patterns]
interesting_counts_table = np.array(map(select_counts, all_counts))
print interesting_counts_table
# Now it's a numpy array, so we can integrate, average sum etc
#print interesting_counts_table
fit_data = np.sum(interesting_counts_table, axis=1)
#print np.sum(interesting_counts_table, axis=1)
print fit_data
raw_input()
return fit_data
def pm_take_fringe(reck_heaters, heater_index, min_voltage, max_voltage, N, int_time, metadata):
pm=powermeter()
keys = ['a','b','c','d','e','f']
#global output_file
output_file = ctx('C:/Users/Qubit/Code/lab_code/Calibration/Calibration/data/', metadata=metadata)
output_file_name = output_file.filename
parameter_space=np.linspace(min_voltage, max_voltage, N)
for index, parameter in enumerate(parameter_space):
print 'Setting voltage %s' % str(parameter)
reck_heaters.send_one_voltage(heater_index, parameter)
time.sleep(1)
total=np.zeros(6)
print reck_heaters.query_v(heater_index)
print pm.read()
for i in range(int_time):
total += np.array(pm.read())
print total
counts_dict = dict(zip(keys, total.tolist()))
output_file.write('count_rates', counts_dict)
current_context=reck_heaters.vip_heater(heater_index)
output_file.write('context', current_context)
pm.kill()
return output_file_name
def parse(datafilename, patterns):
# This loads the CTX file
#dir = os.path.dirname(os.path.realpath(__file__))
#datafilename = os.path.join(dir, '2014_05_13_tuesday_11h57m00s.ctx')
ctxfile = ctx(datafilename)
#print ctxfile
# This pulls out all the stuff to do with count rates
all_counts = list(ctxfile.stream('count_rates'))
# This filters for the count rates we care about
select_counts = lambda data: [
parse_coincidence_pattern(pattern, data) for pattern in patterns
]
interesting_counts_table = np.array(map(select_counts, all_counts))
print interesting_counts_table
# Now it's a numpy array, so we can integrate, average sum etc
#print interesting_counts_table
fit_data = np.sum(interesting_counts_table, axis=1)
#print np.sum(interesting_counts_table, axis=1)
print fit_data
raw_input()
return fit_data
def pm_take_fringe(reck_heaters, heater_index, min_voltage, max_voltage, N,
int_time, metadata):
pm = powermeter()
keys = ['a', 'b', 'c', 'd', 'e', 'f']
#global output_file
output_file = ctx(
'C:/Users/Qubit/Code/lab_code/Calibration/Calibration/data/',
metadata=metadata)
output_file_name = output_file.filename
parameter_space = np.linspace(min_voltage, max_voltage, N)
for index, parameter in enumerate(parameter_space):
print 'Setting voltage %s' % str(parameter)
reck_heaters.send_one_voltage(heater_index, parameter)
time.sleep(1)
total = np.zeros(6)
print reck_heaters.query_v(heater_index)
print pm.read()
for i in range(int_time):
total += np.array(pm.read())
print total
counts_dict = dict(zip(keys, total.tolist()))
output_file.write('count_rates', counts_dict)
current_context = reck_heaters.vip_heater(heater_index)
output_file.write('context', current_context)
pm.kill()
return output_file_name
def take_fringe(reck_heaters, heater_index, min_voltage, max_voltage, N, int_time, metadata):
global output_file
output_file = ctx('C:/Users/Qubit/Code/lab_code/Calibration/Calibration/data/', metadata=metadata)
output_file_name = output_file.filename
parameter_space=np.linspace(min_voltage, max_voltage, N)
# Connect to the counting gear and configure it
counter=coincidence_counter(callback=handle_data)
counter.set_integration_time(int_time)
for index, parameter in enumerate(parameter_space):
print 'Setting voltage %s' % str(parameter)
reck_heaters.send_one_voltage(heater_index, parameter)
current_context=reck_heaters.dict()
counter.count(context=current_context)
# Collect and log the last piece of data from the postprocessor
counter.collect()
# Close connections to hardware
counter.kill()
return output_file_name
from qy.analysis.coincidence_counting import pattern_parser
from matplotlib import pyplot as plt
from glob import glob
import os
'''
An example of reading and processing data from a dip-like measurement
'''
# Get a list of CTX files on the dekstop
all_files=glob('C:/Users/Qubit/Desktop/data_from_example_scripts/*.ctx')
filename=all_files[-1]
# Load up a file for reading
my_file=ctx(filename)
# What do we know about it already?
print my_file
###############################
# Simple reading of data
###############################
# Read out some countrates
for data in my_file.stream('count_rates'):
print 'Raw data:', data
twofolds = pattern_parser.parse_coincidence_pattern('**', data)
print 'Total twofolds (**):', twofolds
# Read out some positions
output_file.write("context", context)
# A less verbose alternative:
# output_file.write('position', context[which_motor]['position'])
# Write count rates to disk
output_file.write("count_rates", count_rates)
elif key == "dpc230_status":
pass
#####################################################
# START HERE
#####################################################
# Get a file ready to store data
metadata = {"label": "This is a test!", "mood": "hungry for knowledge"}
output_file = ctx("C:/Users/Qubit/Desktop/data_from_example_scripts/", metadata=metadata)
# Dip parameters
parameter_space = np.linspace(0, 10, 11)
which_motor = 3
# Connect to the motor controllers
motor_controller = smc100(callback=None)
# Connect to the counting gear and configure it
counter = coincidence_counter(callback=handle_data)
counter.set_integration_time(1)
# Loop over a dip
for position in parameter_space:
print "Moving to position %.3f" % position
''' Check the state of the gui '''
for key, value in interface.collect():
if key=='gui_quit':
sys.exit(0)
elif key=='log_now':
data_file.write('powers', total.tolist())
print 'wrote ', total
# The GUI
interface=gui()
# The meter
powermeter=powermeter()
# Output file
data_file=ctx('data/%s.ctx' % qy.util.timestamp())
data_file.write_metadata({'scan_label':'Looking at bright light'})
total=np.zeros(6)
print data_file
while True:
total=np.zeros(6)
for i in range(10):
total += np.array(powermeter.read())
data=dict(zip('abcdefg', total))
interface.send('count_rates', data)
check_gui()
interface.kill()
interface.send('count_rates', count_rates)
elif key == 'dpc230_status':
interface.send('status', value)
#####################################################
# START HERE
#####################################################
# Dip parameters
parameter_space = np.linspace(0, 10, 11)
which_motor = 3
# Get a file ready to store data
md = {'label': 'This is a test!', 'mood': 'hungry for knowledge'}
output_file = ctx('C:/Users/Qubit/Desktop/data_from_example_scripts/',
metadata=md)
# Make the GUI
interface = gui()
# Connect to the motor controllers
motor_controller = smc100(callback=None)
# Connect to the counting gear and configure it
counter = coincidence_counter(callback=handle_data)
counter.set_integration_time(1)
# Loop over a dip
for position in parameter_space:
print 'Moving to position %.3f' % position
motor_controller.actuators[which_motor].move(position)
