コード例 #1
0
ファイル: sweep_fringe.py プロジェクト: peteshadbolt/lab_code
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
コード例 #2
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ファイル: parse_data.py プロジェクト: peteshadbolt/lab_code
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
コード例 #3
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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


	
コード例 #4
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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
コード例 #5
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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
コード例 #6
0
ファイル: sweep_fringe.py プロジェクト: peteshadbolt/lab_code
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
コード例 #7
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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
コード例 #8
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ファイル: dip_example.py プロジェクト: peteshadbolt/lab_code
            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
コード例 #9
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        ''' 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()
コード例 #10
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            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)