def get_config_screen(self):
"""Returns the current measurements' configuration.
Parameters
----------
nothing
Returns
-------
configuration : dict as {'Source': int, 'Type': str}
It states the source and type of configured measurement.
"""
configuration = {}
xze, xin, yze, ymu, yoff = self.osci.query_ascii_values(
'WFMPRE:XZE?;XIN?;YZE?;YMU?;YOFF?;', separator=';')
configuration.update({
'Source': # channel
find_1st_number(self.osci.query('MEASU:IMM:SOU?'))
})
configuration.update({
'Type': # type of measurement
self.osci.query('MEASU:IMM:TYP?')
})
return configuration
def get_config_measure(self):
"""Returns the current measurements' configuration.
Parameters
----------
nothing
Returns
-------
configuration : dict as {'Source': int, 'Type': str}
It states the source and type of configured measurement.
"""
configuration = {}
configuration.update({
'Source': # channel
find_1st_number(self.osci.query('MEASU:IMM:SOU?'))
})
configuration.update({
'Type': # type of measurement
self.osci.query('MEASU:IMM:TYP?')
})
return configuration
plt.grid()
plt.show()
#%% by Marcos
name = 'Frequency_Sweep'
folder = os.path.join(os.getcwd(), 'Measurements', name)
# Por Fourier:
fourierfiles = sorted([
os.path.join(folder, f) for f in os.listdir(folder)
if f.endswith('Fourier.txt')
])
f = fourierfiles[20]
samplingrate = fstr.find_1st_number(f) * 1.012
actual_freq, fourier_freq, fourier_power = np.loadtxt(f, unpack=True)
#plt.stem(actual_freq, np.ones_like(actual_freq))
#plt.stem(fourier_freq, fourier_power)
#expected curve:
fr = np.arange(actual_freq[0], actual_freq[-1], 100)
fa = np.array([np.abs(fr - n * samplingrate) for n in range(10)])
fa = np.min(fa, axis=0)
yrange = (0, max(fourier_freq) * 1.1) #plotting range
plt.plot(fr, fa, label='Alias de frecuencias esperado', linewidth=2)
plt.plot(actual_freq,
fourier_freq,
'o',
ds = np.diff(signal)
picos = find_peaks(ds, **kwargs)[0]
vel = np.diff(picos).astype(float)
t = time[picos[:-1]]
return t, 1 / vel
#def fix_vel(vel, threshold):
#%%
#Select file and extract stuff
gen_freq = 10e3 #in Hz
file = contenidos_completos[1]
salto = fst.find_numbers(file)[0:1]
samplerate = fst.find_1st_number(retrieve_footer(file)) #in Hz
points_per_gen_period = samplerate / gen_freq
#load data
time, signal, gen = np.loadtxt(file, unpack=True)
signal = np.abs(signal)
gen /= np.mean(gen[gen > 4]) # gen now goes between 0 and 1, approx
cada = 200
#integral = np.array([np.trapz(gen[i:i+cada]) for i in range(len(gen)-cada)])
#duty_cycle = np.array([np.mean(gen[i:i+cada]) for i in range(len(gen)-cada)])
ds = normalize(np.diff(signal), 3)
signal = normalize(signal, 4)
picos = find_peaks(ds, height=.6, prominence=.4)[0]
#vel = np.diff(picos)
def get_config_output(self):
"""Returns current outputs' configuration on a dictionary.
Parameters
----------
nothing
Returns
-------
configuration : dic
Current outputs' configuration.
i.e.: {1:{
'Status': True,
'Waveform': 'SIN',
'Frequency': 1000.0,
'Amplitude': 1.0,
'Offset': 0.0,
'Phase': 0.0,
'Symmetry': 50.0,
'Duty Cycle': 50.0,}}
"""
configuration = {i: dict() for i in range(1, self.nchannels + 1)}
for channel in range(1, self.nchannels + 1):
# On or off?
configuration[channel].update({
'Status':
bool(int(self.gen.query('OUTP{}:STAT?'.format(channel))))
})
# Waveform configuration
configuration[channel].update({
'Waveform':
self.gen.query('SOUR{}:FUNC:SHAP?'.format(channel))
})
# Frequency configuration
aux = self.gen.query('SOUR{}:FREQ?'.format(channel))
configuration[channel]['Frequency'] = find_1st_number(aux)
# Amplitude configuration
aux = self.gen.query('SOUR{}:VOLT:LEV:IMM:AMPL?'.format(channel))
configuration[channel]['Amplitude'] = find_1st_number(aux)
# Offset configuration
aux = self.gen.query('SOUR{}:VOLT:LEV:IMM:OFFS?'.format(channel))
configuration[channel]['Offset'] = find_1st_number(aux)
# Phase configuration
aux = self.gen.query('SOUR{}:PHAS?'.format(channel))
configuration[channel]['Phase'] = find_1st_number(aux)
# PULS's Duty Cycle configuration
try:
aux = self.gen.query('SOUR{}:PULS:DCYC?'.format(channel))
configuration.update({'Duty Cycle': find_1st_number(aux)})
except:
configuration[channel]['Duty Cycle'] = 50.0
# RAMP's Symmetry configuration
try:
aux = self.gen.query('SOUR{}:FUNC:RAMP:SYMM?'.format(channel))
configuration[channel]['Symmetry'] = find_1st_number(aux)
except:
configuration[channel]['Symmetry'] = 50.0
return configuration