def acquire_data(heater_indeces, N=20, DEBUG=False):
min_phase, max_phase = 0, 2 * np.pi
scan = np.linspace(min_phase, max_phase, N)
parameter_space = np.meshgrid(scan, scan)
data = np.zeros([N, N])
# connect hardware
d = dac.dac()
table = calibration_table()
meter = powermeter()
for index_1, parameter_1 in enumerate(scan):
for index_2, parameter_2 in enumerate(scan):
print index_1, index_2
if DEBUG:
data[index_1, index_2] = (1 - index_1 * .03) * fit_func(
[0.2, 0.4, 1, 0], [parameter_1, parameter_2])
else:
# Figure out the settings
voltages = np.zeros(8)
first_heater, second_heater = heater_indeces
voltages[first_heater] = table.get_voltage_from_phase(
first_heater, parameter_1)
voltages[second_heater] = table.get_voltage_from_phase(
second_heater, parameter_2)
print voltages.round(3)
# Do the measurement
d.write_voltages(voltages)
for q in range(10):
meter.read()
intensities = np.zeros(6)
for q in range(6):
intensities += np.array(meter.read())
# cool
d.zero()
for q in range(10):
meter.read()
data[index_1, index_2] = intensities[0]
# Close hardware
d.zero()
meter.kill()
# Normalize, save and return data
data = data / np.amax(data)
data_filename, param_filename = get_filenames(heater_indeces)
np.save(data_filename, data)
np.save(param_filename, parameter_space)
return data_filename, param_filename
def acquire_data(heater_index, N=20, DEBUG=False, hold=[]):
min_phase, max_phase = 0, 2 * np.pi
parameter_space = np.linspace(min_phase, max_phase, N)
data = np.zeros([N])
# connect hardware
d = dac.dac()
table = calibration_table()
meter = powermeter()
for index_1, parameter_1 in enumerate(parameter_space):
print index_1
if DEBUG:
data[index_1] = 0
else:
# Figure out the settings
voltages = np.zeros(8)
voltages[heater_index] = table.get_voltage_from_phase(
heater_index, parameter_1)
# Hold some phases constant during the scan
for index, phase in hold:
voltages[index] = table.get_voltage_from_phase(index, phase)
print voltages.round(3)
# Do the measurement
d.write_voltages(voltages)
for q in range(10):
meter.read()
intensities = np.zeros(6)
for q in range(6):
intensities += np.array(meter.read())
# cool
d.zero()
for q in range(10):
meter.read()
data[index_1] = intensities[0]
# Close hardware
d.zero()
meter.kill()
# Normalize, save and return data
data = data / np.amax(data)
data_filename, param_filename = get_filenames(heater_index)
np.save(data_filename, data)
np.save(param_filename, parameter_space)
return data_filename, param_filename
def acquire_data(heater_index, N=20, DEBUG=False, hold=[]):
min_phase, max_phase=0, 2*np.pi
parameter_space=np.linspace(min_phase, max_phase, N)
data=np.zeros([N])
# connect hardware
d=dac.dac()
table=calibration_table()
meter=powermeter()
for index_1, parameter_1 in enumerate(parameter_space):
print index_1
if DEBUG:
data[index_1] = 0
else:
# Figure out the settings
voltages=np.zeros(8)
voltages[heater_index]=table.get_voltage_from_phase(heater_index, parameter_1)
# Hold some phases constant during the scan
for index, phase in hold:
voltages[index]=table.get_voltage_from_phase(index, phase)
print voltages.round(3)
# Do the measurement
d.write_voltages(voltages)
for q in range(10):
meter.read()
intensities=np.zeros(6)
for q in range(6):
intensities+=np.array(meter.read())
# cool
d.zero()
for q in range(10):
meter.read()
data[index_1] = intensities[0]
# Close hardware
d.zero()
meter.kill()
# Normalize, save and return data
data=data/np.amax(data)
data_filename, param_filename = get_filenames(heater_index)
np.save(data_filename, data)
np.save(param_filename, parameter_space)
return data_filename, param_filename
def acquire_data(heater_indeces, N=20, DEBUG=False):
min_phase, max_phase=0, 2*np.pi
scan=np.linspace(min_phase, max_phase, N)
parameter_space=np.meshgrid(scan, scan)
data=np.zeros([N,N])
# connect hardware
d=dac.dac()
table=calibration_table()
meter=powermeter()
for index_1, parameter_1 in enumerate(scan):
for index_2, parameter_2 in enumerate(scan):
print index_1, index_2
if DEBUG:
data[index_1, index_2] = (1-index_1*.03)*fit_func([0.2,0.4,1,0], [parameter_1, parameter_2])
else:
# Figure out the settings
voltages=np.zeros(8)
first_heater, second_heater=heater_indeces
voltages[first_heater]=table.get_voltage_from_phase(first_heater, parameter_1)
voltages[second_heater]=table.get_voltage_from_phase(second_heater, parameter_2)
print voltages.round(3)
# Do the measurement
d.write_voltages(voltages)
for q in range(10):
meter.read()
intensities=np.zeros(6)
for q in range(6):
intensities+=np.array(meter.read())
# cool
d.zero()
for q in range(10):
meter.read()
data[index_1, index_2] = intensities[0]
# Close hardware
d.zero()
meter.kill()
# Normalize, save and return data
data=data/np.amax(data)
data_filename, param_filename = get_filenames(heater_indeces)
np.save(data_filename, data)
np.save(param_filename, parameter_space)
return data_filename, param_filename
return experiment_filename, theory_filename, param_filename
start_time = timestamp()
device = lo.beamsplitter_network(json='cnot_mz.json')
simulator = lo.simulator(device, nphotons=2)
simulator.set_input_state([1, 3])
simulator.set_visibility(0.99)
dac = dac.dac()
fpga = fpga()
fpga.read()
fpga.read()
fpga.read()
fpga.read()
table = calibration_table()
heater_index = 6
#hold_table=[[0,pi/2],[2,0], [6,pi/2]]
hold_table = list(enumerate([pi, 0, 0, 0, 0, 0, 0, 0]))
# Take data
acquire_data(heater_index, hold=hold_table, N=40)
# Reload and fit
experiment_filename, theory_filename, param_filename, hold_table_filename = get_filenames(
heater_index)
experiment = np.load(experiment_filename)
theory = np.load(theory_filename)
parameter_space = np.load(param_filename)
plot_now(experiment, theory, parameter_space, do_fit=True)
np.save(experiment_filename, experiment)
np.save(theory_filename, theory)
np.save(param_filename, parameter_space)
return experiment_filename, theory_filename, param_filename
start_time=timestamp()
device=lo.beamsplitter_network(json='cnot_mz.json')
simulator=lo.simulator(device, nphotons=2)
simulator.set_input_state([1,3])
simulator.set_visibility(0.95)
dac=dac.dac()
fpga=fpga()
fpga.read()
fpga.read()
fpga.read()
fpga.read()
table=calibration_table()
heater_index = 5
#hold_table=[[0,pi/2],[2,0], [6,pi/2]]
hold_table=list(enumerate([0,pi/2,0,0,0,0,0,pi/2]))
# Take data
acquire_data(heater_index, hold=hold_table, N=40)
# Reload and fit
#experiment_filename, theory_filename, param_filename = get_filenames(heater_index)
#experiment=np.load(experiment_filename)
#theory=np.load(theory_filename)
#parameter_space=np.load(param_filename)