import numpy as np
import nicenquickplotlib as nq
x = []
x.append(np.linspace(0,6))
x.append(np.linspace(0,5))
x.append(np.linspace(0,4))
nq.set_figstyle('default')
nq.plot(x, [np.sin(x[0]), np.cos(x[1]), np.sqrt(x[2])], legend=[r'$\sin(x)$', r'$\cos(x)$', r'$\sqrt{x}$'], xlabel='x label', ylabel='y label')
nq.set_figstyle('blacknwhite')
nq.plot(x, [np.sin(x[0]), np.cos(x[1]), np.sqrt(x[2])], legend=[r'$\sin(x)$', r'$\cos(x)$', r'$\sqrt{x}$'], xlabel='x label', ylabel='y label')
nq.set_figstyle('soft')
nq.plot(x, [np.sin(x[0]), np.cos(x[1]), np.sqrt(x[2])], legend=[r'$\sin(x)$', r'$\cos(x)$', r'$\sqrt{x}$'], xlabel='x label', ylabel='y label')
nq.set_figstyle('my_figstyle.yaml')
nq.plot(x, [np.sin(x[0]), np.cos(x[1]), np.sqrt(x[2])], legend=[r'$\sin(x)$', r'$\cos(x)$', r'$\sqrt{x}$'], xlabel='x label', ylabel='y label')
nq.save_all()
for k in range(len(DMM)):
DMM[k].write('RESET')
FunGen.write('RESET')
print('Instruments have been reset.')
for k in range(len(DMM)):
DMM[k].read_termination = HP3458A.read_termination
FunGen.read_termination = HP3458A.read_termination
# Measure --------------------------------------------------------------
for k in range(len(GENERATOR_FREQUENCIES)):
timestamp = utils.timestamp.generate_timestamp()
samples, sampling_frequency = measure_burst(FunGen=FunGen, DMM=DMM, generator_frequency=GENERATOR_FREQUENCIES[k], generator_amplitude=GENERATOR_AMPLITUDE, sampling_frequency=SAMPLING_FREQUENCIES[k], number_of_samples=SAMPLES_PER_BURST, verbose=True)
with open(DIRS.UNPROCESSED_DATA_PATH + timestamp + DIRS.CONFIG_FILE_SUFFIX, 'w') as ofile:
print('Generator frequency (Hz)\tSampling frequency (Hz)\tGenerator amplitude (V)', file=ofile)
print(str(GENERATOR_FREQUENCIES[k]) + '\t' + str(sampling_frequency) + '\t' + str(GENERATOR_AMPLITUDE), file=ofile)
with open(DIRS.UNPROCESSED_DATA_PATH + timestamp + DIRS.SAMPLES_FILE_SUFFIX, 'w') as ofile:
print('Samples1 (V)\tSamples2 (V)', file=ofile)
for k in range(len(samples[0])):
print(str(samples[0][k].n) + '\t' + str(samples[1][k].n), file=ofile)
# Close instruments ----------------------------------------------------
print('Closing instruments...')
for k in range(len(DMM)):
DMM[k].write('DISP OFF, \'I am DMM[' + str(k) + ']\'')
DMM[k].close()
FunGen.write('USE CHANA') # Select channel A to receive subsequent commands.
FunGen.write('TERM OFF') # Disconnect the output from all terminals.
FunGen.write('USE CHANB') # Select channel B to receive subsequent commands.
FunGen.write('TERM OFF') # Disconnect the output from all terminals.
FunGen.close()
print('Saving data...')
nq.save_all(timestamp=True, csv=True)
legend=r'$\sin (x)$',
title='legend passing the legend as a string')
nq.plot(x[0],
np.sin(x[0]),
legend=[r'$\sin (x)$'],
title='legend passing the legend as a list')
nq.plot(x,
[np.sin(x[0]), np.cos(x[1]), np.sqrt(x[2])],
legend=[r'$\sin(x)$', r'$\cos(x)$', r'$\sqrt{x}$'],
title='legend multiple legends together')
nq.plot(x,
[np.sin(x[0]), np.cos(x[1]), np.sqrt(x[2])],
legend=[r'$\sin(x)$', r'$\cos(x)$', r'$\sqrt{x}$'],
together=False,
title='legend multiple legends together=False')
nq.save_all(timestamp='now')
# Test colors -----------------------------
random_y = []
for k in range(10):
random_y.append(np.random.normal(loc=k, size=10))
nq.set_figstyle('default')
nq.plot(random_y, title='colors')
# Test markers ----------------------------
nq.plot(x,
[np.sin(x[0]), np.cos(x[1]), np.sqrt(x[2])],
legend=[r'$\sin(x)$', r'$\cos(x)$', r'$\sqrt{x}$'],
marker=True,
title='markers default')
nq.plot(x,
[np.sin(x[0]), np.cos(x[1]), np.sqrt(x[2])],
legend=[r'$\sin(x)$', r'$\cos(x)$', r'$\sqrt{x}$'],
import nicenquickplotlib as nq
import uncertainties as unc # https://pythonhosted.org/uncertainties/index.html
import numpy as np
x = np.linspace(0, 2, 10) # Create x data.
y_vals_1 = x**2 # Create y_1 data.
y_errs_1 = y_vals_1 * 0.1 + np.random.rand(len(x)) * 0.1 # Create y_1 errors.
y_vals_2 = np.sqrt(x) # Create y_2 data.
y_errs_2 = y_vals_2 * 0.1 + np.random.rand(len(x)) * 0.1 # Create y_2 errors.
y_1 = unc.unumpy.uarray(y_vals_1,
y_errs_1) # Create y_1 array of uncertainties.
y_2 = unc.unumpy.uarray(y_vals_2,
y_errs_2) # Create y_2 array of uncertainties.
nq.plot(x, [y_1, y_2],
title='y error bands',
legend=['Data 1', 'Data 2'],
marker=True)
nq.set_figstyle('blacknwhite')
nq.plot(x, [y_1, y_2],
title='y error bands with blacknwhite figstyle',
legend=['Data 1', 'Data 2'],
marker=True)
nq.save_all(csv=True)
freq = np.array(freq)
# PLOT ----------------------------
nq.plot(x=freq,
y=[T_abs_definitive, T_phi_definitive],
together=False,
xlabel='Frequency (Hz)',
ylabel=['Ratio', 'Phase (rad)'],
xscale='L',
title='Transference',
marker='.')
nq.plot(
x=freq,
y=[
unp.std_devs(T_abs_definitive) / unp.nominal_values(T_abs_definitive),
np.abs(
unp.std_devs(T_phi_definitive) /
unp.nominal_values(T_phi_definitive))
],
together=False,
xlabel='Frequency (Hz)',
ylabel=[
r'Ratio err $\frac{\sigma}{\mu}$', r'Phase err $\frac{\sigma}{\mu}$'
],
xscale='L',
yscale='L',
title='Transference uncertainties',
marker='.')
nq.save_all(mkdir=DIRS.TRANSFERENCE_RESULTS_PATH, csv=True)
print('Transference has been plotted and data was saved in ' +
DIRS.TRANSFERENCE_RESULTS_PATH)
ylabel='Voltage (V)',
nicebox=True,
marker='.')
fig.axes[-1].set_xlim(
[0, 10 * sampling_frequency / 2 / np.pi / generator_frequency])
# Transference calculation ---------------
T_abs = discrete_time_model[1].param_val(0) / discrete_time_model[0].param_val(
0)
T_phi = utils.lock_in_process.lock_in_process(samples[0], samples[1])
T_abs = np.abs(
T_abs
) # This is because sometimes the fitting algorithm converges to a negative amplitude.
# Save data ------------------------------
os.rename(
DIRS.CURRENTLY_PROCESSING_DATA_PATH + current_timestamp +
DIRS.CONFIG_FILE_SUFFIX,
DIRS.PROCESSED_DATA_PATH + current_timestamp + DIRS.CONFIG_FILE_SUFFIX)
os.rename(
DIRS.CURRENTLY_PROCESSING_DATA_PATH + current_timestamp +
DIRS.SAMPLES_FILE_SUFFIX,
DIRS.PROCESSED_DATA_PATH + current_timestamp + DIRS.SAMPLES_FILE_SUFFIX)
nq.save_all(mkdir=DIRS.PROCESSED_DATA_PATH + current_timestamp + 'plots')
with open(
DIRS.PROCESSED_DATA_PATH + current_timestamp +
DIRS.TRANSFERENCE_FILE_SUFFIX, 'w') as ofile:
print('T_abs.n\tT_abs.s\tT_phi.n', file=ofile)
print(str(T_abs.n) + '\t' + str(T_abs.s) + '\t' + str(T_phi), file=ofile)
print('Analysis completed.')
print('Original data and results can be found in "' +
DIRS.PROCESSED_DATA_PATH + '"')
fungen.write('OUTP1:IMP INF'
) # Set the output impedance to zero (infinite load impedance).
fungen.write('voltage {}'.format(GENERATOR_AMPLITUDE))
fungen.write('voltage:offset {}'.format(GENERATOR_AMPLITUDE / 2))
fungen.write(':frequency:fixed {}'.format(
GENERATOR_FREQUENCY)) #sets function generator frequency
fungen.write('source1:function:shape squ')
little_board = cf.Little_Board('Dev11')
fungen.write('OUTP1:STAT ON')
time.sleep(1)
data = np.array(
little_board.acquire(n_samples=N_SAMPLES,
sampling_frequency=GENERATOR_FREQUENCY * N_SAMPLES /
N_CYCLES,
ch0=True,
ch1=True))
time_axis = np.linspace(0, N_CYCLES / GENERATOR_FREQUENCY, N_SAMPLES)
nq.plot(x=time_axis,
y=[np.array(data[0]), np.array(data[1])],
together=False,
xlabel='Tiempo (s)')
fungen.write('OUTP1:STAT OFF')
fungen.close()
nq.save_all(timestamp=True, image_format='pdf', csv=True)
nq.show()
import numpy as np
import nicenquickplotlib as nq
x = []
x.append(np.linspace(0, 6))
x.append(np.linspace(0, 5))
x.append(np.linspace(0, 4))
nq.set_figstyle('default')
nq.plot(x,
[np.sin(x[0]), np.cos(x[1]), np.sqrt(x[2])],
legend=[r'$\sin(x)$', r'$\cos(x)$', r'$\sqrt{x}$'],
xlabel='x label',
ylabel='y label')
nq.set_figstyle('blacknwhite')
nq.plot(x,
[np.sin(x[0]), np.cos(x[1]), np.sqrt(x[2])],
legend=[r'$\sin(x)$', r'$\cos(x)$', r'$\sqrt{x}$'],
xlabel='x label',
ylabel='y label')
nq.set_figstyle('soft')
nq.plot(x,
[np.sin(x[0]), np.cos(x[1]), np.sqrt(x[2])],
legend=[r'$\sin(x)$', r'$\cos(x)$', r'$\sqrt{x}$'],
xlabel='x label',
ylabel='y label')
nq.save_all(image_format='pdf')