def output_swing_plot(data, fig, error_plot=False):
vcc = data.vcc
extend(data)
fw = FigureWrapper(
data, fig,
x='voltage',
y='error' if error_plot else 'voltage',
title='Maximum peak output voltage swing')
yname = 'Vout_diff' if error_plot else 'Vout'
for R in Rloads(data):
fw.addcol(legend=unicode(format_ohm(R) if R else R),
x='Vout_expected',
y=yname,
filter_func=get_filter_func(R, 'output_swing'),
sortbyx=True,
)
ax = fw.subplot
# ax.legend(*ax.get_legend_handles_labels(), loc='upper center')
ax.set_xlabel('Expected (V)')
# ax.grid(True)
# ax.axvline(x=0, color='black')
# ax.axvline(x=dw.data.vcc, color='black')
# ax.axhline(y=0, color='black')
if error_plot:
ax.set_ylabel('error (V)')
# ax.axis([0, 5.1, -0.2, 0.2])
else:
# ax.axhline(y=dw.data.vcc, color='black')
ax.plot([0, vcc], [0, vcc])
# ax.axis([0, 5.1, 0, 5.1])
ax.set_ylabel('Real (V)')
return fig
def analog_value_time_plot(data, fig, voltage=False):
fw = FigureWrapper(data, fig, x='time', y='analog_value',
convert2voltage=voltage)
fw.addcol(legend='volt', y='Avolt')
fw.addcol(legend='current', y='Acurrent')
return fig
def transfer_plot(data, fig):
title = 'Voltage Transfer Curve'
extend(data)
fw = FigureWrapper(
data,
fig,
x='Vin (V)',
y='Vout (V)',
title=title,
# xlimits=[-5, 5],
# ylimits=[-0.020, 0.020],
)
fw.subplot.plot(
[0, data.Vmax],
[0, data.Vmax],
'r-')
fw.subplot.plot(
[0, data.Vmax],
[data.Vmax, 0],
'r-')
# fw.addcol(legend='', x='Vin', y='Vout')
fw.addcol(legend='up',
x='Vin',
y='Vout',
filter_func=lambda e: e.reverse == 0,
)
fw.addcol(legend='down',
x='Vin',
y='Vout',
filter_func=lambda e: e.reverse == 1,
)
return fig
def IV_curve_plot(data, fig):
title = 'I/O pin current vs. output voltage'
extend(data)
fw = FigureWrapper(
data,
fig,
x='voltage',
y='I (A)',
title=title,
xlimits=[-5, 5],
ylimits=[-0.020, 0.020],
)
x = 'Vx'
y = 'I'
fw.subplot.plot(
[0, data.Vmax],
[data.Imax, 0],
'b-')
fw.subplot.plot(
[0, -data.Vmax],
[-data.Imax, 0],
'b-')
fw.addcol(legend='', x=x, y=y)
return fig
def analog_value_time_plot(data, fig, voltage=False):
fw = FigureWrapper(
data, fig, x='time', y='analog_value', convert2voltage=voltage)
fw.addcol(legend='out', y=lambda e: e.Aout)
fw.addcol(legend='amp', y=lambda e: e.Aamp)
return fig
def transfer_plot(data, fig, error_plot=False):
data.measurements = filter_measurements(data.measurements, ['pwm_value'],
['Ain'])
title = 'Transfer error plot (%s)' if error_plot else 'Transfer plot (%s)'
title = title % (data.model)
fw = FigureWrapper(
data,
fig,
x='voltage',
y='error (V)' if error_plot else 'voltage',
title=title,
)
vcc = data.vcc
fw.addcol(
legend=data.config.pin_in,
x=lambda e: pwm2v(e.pwm_value, vcc),
y=lambda e: an2v(e.Ain, vcc) - (pwm2v(e.pwm_value, vcc)
if error_plot else 0),
)
ax = fw.subplot
if error_plot:
ax.axis([0, 5.1, -0.050, 0.050])
return fig
def transfer_plot(data, fig, error_plot=False):
data.measurements = filter_measurements(data.measurements, ['value'],
['Ain'])
title = 'Transfer error plot' if error_plot else 'Transfer plot'
title = title
fw = FigureWrapper(
data,
fig,
x='voltage',
y='error (V)' if error_plot else 'voltage',
title=title,
)
vcc = data.vcc
if error_plot:
fw.subplot.plot([0, vcc], [vcc / 99, vcc / 99], 'r-')
fw.subplot.plot([0, vcc], [-vcc / 99, -vcc / 99], 'r-')
else:
fw.subplot.plot([0, 0], [vcc, vcc], 'r-')
fw.addcol(
legend=data.config.pin_in,
x=lambda e: pot2v(e.value, vcc),
y=lambda e: an2v(e.Ain, vcc) - (pot2v(e.value, vcc)
if error_plot else 0),
)
ax = fw.subplot
if error_plot:
ax.axis([0, 5.1, -0.1, 0.1])
return fig
def dig_input_plot(data, fig):
title = 'Digital input characteristic %s@%s' % (data.config.pin_dig_in, data.model)
fw = FigureWrapper(
data,
fig,
x='VCC percentage',
y='digital in',
title=title,
ylimits=[-0.5, 1.5],
)
def fperc(e):
return e.Ain * 100 / 1023
fw.addcol(legend='up',
x=fperc,
y='Din',
filter_func=lambda e: e.reverse == 0,
)
fw.addcol(legend='down',
x=fperc,
y='Din',
filter_func=lambda e: e.reverse == 1,
)
return fig
def analog_value_time_plot(data, fig, voltage=False):
fw = FigureWrapper(
data, fig, x='time', y='analog_value', convert2voltage=voltage)
fw.addcol(legend='analog in', y=lambda e: e.Ain)
fw.addcol(legend='digital in', y=lambda e: e.Din * 1023)
return fig
def input_range_plot(data, fig, error_plot=False):
vcc = data.vcc
extend(data)
fw = FigureWrapper(
data,
fig,
x='voltage',
y='error' if error_plot else 'voltage',
title='Common-mode input voltage range')
# print data.measurements
yname = 'Vin_diff' if error_plot else 'Vopamp_minus'
for R in [NO_LOAD]:
fw.addcol(legend='',
x='Vplus',
y=yname,
filter_func=get_filter_func(R, 'input_range'),
)
ax = fw.subplot
ax.set_xlabel('opamp+ (V)')
# ax.grid(True)
# ax.axvline(x=0, color='black')
# ax.axvline(x=dw.data.vcc, color='black')
if error_plot:
# ax.axhline(y=0, color='black')
ax.set_ylabel('error (V)')
# ax.axis([0, 5.1, -0.050, 0.050])
else:
ax.plot([0, vcc], [0, vcc])
# ax.axis([0, 5.1, 0, 5.1])
ax.set_ylabel('opamp- (V)')
return fig
def analog_value_time_plot(data, fig, voltage=False):
fw = FigureWrapper(
data, fig, x='time', y='analog_value', convert2voltage=voltage)
fw.addcol(y='Ab')
fw.addcol(y='Ac')
return fig
def analog_value_time_plot(data, fig, voltage=False):
fw = FigureWrapper(data, fig, x="time", y="analog_value", convert2voltage=voltage)
# fw.addcol(legend=data.config.pin_in, y='Ain')
# fw.addcol(legend='%s relativ PWM' % data.config.pin_pwm,
# y=lambda e: e.value / 255 * 1023)
fw.addcol(y="Ain")
fw.addcol(y="value")
return fig
def analog_value_time_plot(data, fig, voltage=False):
fw = FigureWrapper(
data, fig, x='time', y='analog_value', convert2voltage=voltage)
legend = data['config']['pin']
fw.addcol(legend=legend,
y='A',
)
return fig
def analog_value_time_plot(data, fig, voltage=False):
fw = FigureWrapper(
data, fig, x='time', y='analog_value', convert2voltage=voltage)
fw.addcol(legend='top', y=lambda e: e.get('Atop'))
fw.addcol(legend='middle', y=lambda e: e.get('Amiddle'))
fw.addcol(legend='bottom', y=lambda e: e.get('Abottom'))
return fig
def analog_value_time_plot(data, fig, voltage=False):
fw = FigureWrapper(data,
fig,
x='time',
y='analog_value',
convert2voltage=voltage)
fw.addcol(legend='in', y='Ain')
return fig
def analog_value_time_plot(data, fig, voltage=False):
fw = FigureWrapper(
data, fig, x='time', y='analog_value', convert2voltage=voltage)
# fw.addcol(legend='rel pwm', y=lambda e: e.pwm_value/255*1023)
fw.addcol(legend='in', y='Ain')
fw.addcol(legend='out', y='Aout')
fw.addcol(legend='amp', y='Aamp')
return fig
def frequency_time_plot(data, fig):
fw = FigureWrapper(data, fig, x='time', y='frequency', draw_axis=False)
fw.addcol(y='frequency')
# fw.subplot.set_ylim(bottom=100000)
# fw.subplot.set_ylim(auto=True)
# ax = fw.subplot
# ax.set_autoscale_on(True)
# ax.autoscale_view(True,False,True)
return fig
def frequency_time_plot(data, fig):
fw = FigureWrapper(data, fig, x="time", y="frequency", draw_axis=False)
fw.addcol(y="frequency")
# fw.subplot.set_ylim(bottom=100000)
# fw.subplot.set_ylim(auto=True)
# ax = fw.subplot
# ax.set_autoscale_on(True)
# ax.autoscale_view(True,False,True)
return fig
def processed_analog_value_time_plot(data, fig):
fw = FigureWrapper(
data, fig, x='time', y='voltage')
extend(data)
fw.addcol(legend='Vin', y='Vin')
fw.addcol(legend='Vout', y='Vout')
fw.addcol(legend='Vamp', y='Vamp')
return fig
def processed_analog_value_time_plot(data, fig):
fw = FigureWrapper(data, fig, x='time', y='voltage')
extend(data)
# fw.addcol(legend='rel pwm', y=lambda e: e.pwm_value/255*1023)
fw.addcol(legend='Vin', y=lambda e: e.Vin)
fw.addcol(legend='Vout', y=lambda e: e.Vout)
fw.addcol(legend='Vamp', y=lambda e: e.Vamp)
fw.addcol(legend='Vx', y=lambda e: e.Vx)
fw.addcol(legend='I', y=lambda e: e.I)
return fig
def analog_value_time_plot(data, fig, voltage=False):
fw = FigureWrapper(data,
fig,
x='time',
y='analog_value',
convert2voltage=voltage)
# fw.addcol(legend='top', y='Atop')
fw.addcol(legend='middle', y='Amiddle')
# fw.addcol(legend='bottom', y='Abottom')
return fw
def ohm_plot(data, fig):
d = analyse1(data)
# print d
newdata = dict(measurements=d, project='esr')
# print 676,newdata
fw = FigureWrapper(newdata, fig, x='frequency', y='R')
fw.addcol(x='frequency', y='Rx')
ax = fw.subplot
ax.set_xscale('log')
# ax.set_yscale('log')
return fig
def unity_gain_plot(data, fig, error_plot=False):
# dw = DataWrapper(data)
config = data.config
vcc = data.vcc
measurements = data.measurements
# A = config.R2 / config.R1
extend(data)
fw = FigureWrapper(data,
fig,
x='voltage',
y='error' if error_plot else 'voltage',
title='Unity gain')
# ax = fig.add_subplot(111)
yname = 'Vout_diff' if error_plot else 'Vout'
for R in [NO_LOAD]:
fw.addcol(
legend='',
x='Vout_expected',
y=yname,
filter_func=get_filter_func(R, 'unity_gain'),
)
ax = fw.subplot
ax.set_xlabel('Vout_expected (V)')
# ax.grid(True)
# ax.axvline(x=0, color='black')
# ax.axvline(x=dw.data.vcc, color='black')
if error_plot:
limit = 0.050
ax.axhline(y=limit, color='red')
ax.axhline(y=-limit, color='red')
# TODO: vlines
# interv = calculate_good_interval(config, measurements, limit=limit)
# if interv:
# ax.axvline(x=interv[0], color='red')
# ax.axvline(x=interv[1], color='red')
ax.axhline(y=0, color='black')
ax.set_ylabel('error (V)')
# ax.axis([0, 5.1, -0.5, 0.5])
else:
ax.plot([0, vcc], [0, vcc])
# ax.axis([0, 5.1, 0, 5.1])
ax.set_ylabel('Vout (V)')
return fig
def ohm_plot(data, fig):
d = analyse1(data)
# print d
newdata = dict(measurements=d, project='esr')
# print 676,newdata
fw = FigureWrapper(
newdata, fig, x='frequency', y='R')
fw.addcol(x='frequency', y='Rx')
ax = fw.subplot
ax.set_xscale('log')
# ax.set_yscale('log')
return fig
def unity_gain_plot(data, fig, error_plot=False):
# dw = DataWrapper(data)
config = data.config
vcc = data.vcc
measurements = data.measurements
# A = config.R2 / config.R1
extend(data)
fw = FigureWrapper(
data, fig,
x='voltage',
y='error' if error_plot else 'voltage',
title='Unity gain')
# ax = fig.add_subplot(111)
yname = 'Vout_diff' if error_plot else 'Vout'
for R in [NO_LOAD]:
fw.addcol(legend='',
x='Vout_expected',
y=yname,
filter_func=get_filter_func(R, 'unity_gain'),
)
ax = fw.subplot
ax.set_xlabel('Vout_expected (V)')
# ax.grid(True)
# ax.axvline(x=0, color='black')
# ax.axvline(x=dw.data.vcc, color='black')
if error_plot:
limit = 0.050
ax.axhline(y=limit, color='red')
ax.axhline(y=-limit, color='red')
# TODO: vlines
# interv = calculate_good_interval(config, measurements, limit=limit)
# if interv:
# ax.axvline(x=interv[0], color='red')
# ax.axvline(x=interv[1], color='red')
ax.axhline(y=0, color='black')
ax.set_ylabel('error (V)')
# ax.axis([0, 5.1, -0.5, 0.5])
else:
ax.plot([0, vcc], [0, vcc])
# ax.axis([0, 5.1, 0, 5.1])
ax.set_ylabel('Vout (V)')
return fig
def processed_analog_value_time_plot(data, fig):
fw = FigureWrapper(
data, fig, x='time', y='voltage')
extend(data)
# fw.addcol(legend='rel pwm', y=lambda e: e.pwm_value/255*1023)
fw.addcol(legend='Vin', y=lambda e: e.Vin)
fw.addcol(legend='Vout', y=lambda e: e.Vout)
fw.addcol(legend='Vamp', y=lambda e: e.Vamp)
fw.addcol(legend='Vx', y=lambda e: e.Vx)
fw.addcol(legend='I', y=lambda e: e.I)
return fig
def frequency_time_plot(data, fig):
title = 'Frequency (gate time=%s s)' % (data.config.gate_time)
fw = FigureWrapper(
data,
fig,
x='time',
y='frequency',
draw_axis=False,
title=title,
)
fw.addcol(y='frequency')
# fw.subplot.set_ylim(bottom=100000)
# fw.subplot.set_ylim(auto=True)
# ax = fw.subplot
# ax.set_autoscale_on(True)
# ax.autoscale_view(True,False,True)
return fig
def frequency_time_plot(data, fig):
title = 'Frequency (gate time=%s s)' % (data.config.gate_time)
fw = FigureWrapper(
data,
fig,
x='time',
y='frequency',
draw_axis=False,
title=title,
)
fw.addcol(y='frequency')
# fw.subplot.set_ylim(bottom=100000)
# fw.subplot.set_ylim(auto=True)
# ax = fw.subplot
# ax.set_autoscale_on(True)
# ax.autoscale_view(True,False,True)
return fig
def analog_value_time_plot(data, fig, voltage=False):
fw = FigureWrapper(data,
fig,
x='time',
y='analog_value',
convert2voltage=voltage)
fw.addcol(legend='plus', y='Aplus')
fw.addcol(legend='minus', y='Aminus')
fw.addcol(legend='out', y='Aout')
return fig
def analog_value_time_plot(data, fig, voltage=False):
fw = FigureWrapper(
data, fig, x='time', y='analog_value', convert2voltage=voltage)
fw.addcol(legend='plus', y='Aplus')
fw.addcol(legend='minus', y='Aminus')
fw.addcol(legend='out', y='Aout')
return fig
def dig_input_plot(data, fig):
title = 'Digital input characteristic %s@%s' % (data.config.pin_dig_in,
data.model)
fw = FigureWrapper(
data,
fig,
x='VCC percentage',
y='digital in',
title=title,
ylimits=[-0.5, 1.5],
)
def fperc(e):
return e.Ain * 100 / 1023
fw.addcol(
legend='up',
x=fperc,
y='Din',
filter_func=lambda e: e.reverse == 0,
)
fw.addcol(
legend='down',
x=fperc,
y='Din',
filter_func=lambda e: e.reverse == 1,
)
return fig
def transfer_plot(data, fig):
title = 'Voltage Transfer Curve'
extend(data)
fw = FigureWrapper(
data,
fig,
x='Vin (V)',
y='Vout (V)',
title=title,
# xlimits=[-5, 5],
# ylimits=[-0.020, 0.020],
)
fw.subplot.plot([0, data.Vmax], [0, data.Vmax], 'r-')
fw.subplot.plot([0, data.Vmax], [data.Vmax, 0], 'r-')
# fw.addcol(legend='', x='Vin', y='Vout')
fw.addcol(
legend='up',
x='Vin',
y='Vout',
filter_func=lambda e: e.reverse == 0,
)
fw.addcol(
legend='down',
x='Vin',
y='Vout',
filter_func=lambda e: e.reverse == 1,
)
return fig
def IV_curve_plot(data, fig):
title = 'I/O pin current vs. output voltage'
extend(data)
fw = FigureWrapper(
data,
fig,
x='voltage',
y='I (A)',
title=title,
xlimits=[-5, 5],
ylimits=[-0.020, 0.020],
)
x = 'Vx'
y = 'I'
fw.subplot.plot([0, data.Vmax], [data.Imax, 0], 'b-')
fw.subplot.plot([0, -data.Vmax], [-data.Imax, 0], 'b-')
fw.addcol(legend='', x=x, y=y)
return fig
def ohm_invf_plot(data, fig):
d = analyse1(data)
# print d
measurements = d
newdata = dict(measurements=d, project='esr')
# print 676,newdata
fw = FigureWrapper(
newdata, fig, x='1/frequency', y='Rx')
# def xtransform(f):
# return 1000000 / (2 * 3.141 * f)
fw.addcol(x=lambda e: 1 / (e.frequency), y='Rx')
ax = fw.subplot
# fmin = filter(lambda e: e['Rx'] is not None, measurements)[0]['frequency']
fmin = min(measurements['frequency'])
# assert 0 ,fmin
ax.set_autoscale_on(False)
# @traced
def Xc(f, c):
return 1 / (2 * np.pi * f * c / 1e6)
ax.plot([0, 1 / (fmin)], [0, Xc(fmin, 0.1)], label='100n')
ax.plot([0, 1 / (fmin)], [0, Xc(fmin, 1)], label='1u')
ax.plot([0, 1 / (fmin)], [0, Xc(fmin, 10)], label='10u')
ax.plot([0, 1 / (fmin)], [0, Xc(fmin, 100)], label='100u')
ax.plot([0, 1 / (fmin)], [0, Xc(fmin, 1000)], label='1000u')
fw.update_legend()
def formatter(x, pos):
if x:
return int(1.0 / x)
else:
return np.inf
ax.xaxis.set_major_formatter(FuncFormatter(formatter))
return fig
def processed_analog_value_time_plot(data, fig):
fw = FigureWrapper(data, fig, x='time', y='voltage')
extend(data)
fw.addcol(legend='Vin', y='Vin')
fw.addcol(legend='Vout', y='Vout')
fw.addcol(legend='Vamp', y='Vamp')
return fig
def input_range_plot(data, fig, error_plot=False):
vcc = data.vcc
extend(data)
fw = FigureWrapper(data,
fig,
x='voltage',
y='error' if error_plot else 'voltage',
title='Common-mode input voltage range')
# print data.measurements
yname = 'Vin_diff' if error_plot else 'Vopamp_minus'
for R in [NO_LOAD]:
fw.addcol(
legend='',
x='Vplus',
y=yname,
filter_func=get_filter_func(R, 'input_range'),
)
ax = fw.subplot
ax.set_xlabel('opamp+ (V)')
# ax.grid(True)
# ax.axvline(x=0, color='black')
# ax.axvline(x=dw.data.vcc, color='black')
if error_plot:
# ax.axhline(y=0, color='black')
ax.set_ylabel('error (V)')
# ax.axis([0, 5.1, -0.050, 0.050])
else:
ax.plot([0, vcc], [0, vcc])
# ax.axis([0, 5.1, 0, 5.1])
ax.set_ylabel('opamp- (V)')
return fig
def output_swing_plot(data, fig, error_plot=False):
vcc = data.vcc
extend(data)
fw = FigureWrapper(data,
fig,
x='voltage',
y='error' if error_plot else 'voltage',
title='Maximum peak output voltage swing')
yname = 'Vout_diff' if error_plot else 'Vout'
for R in Rloads(data):
fw.addcol(
legend=unicode(format_ohm(R) if R else R),
x='Vout_expected',
y=yname,
filter_func=get_filter_func(R, 'output_swing'),
sortbyx=True,
)
ax = fw.subplot
# ax.legend(*ax.get_legend_handles_labels(), loc='upper center')
ax.set_xlabel('Expected (V)')
# ax.grid(True)
# ax.axvline(x=0, color='black')
# ax.axvline(x=dw.data.vcc, color='black')
# ax.axhline(y=0, color='black')
if error_plot:
ax.set_ylabel('error (V)')
# ax.axis([0, 5.1, -0.2, 0.2])
else:
# ax.axhline(y=dw.data.vcc, color='black')
ax.plot([0, vcc], [0, vcc])
# ax.axis([0, 5.1, 0, 5.1])
ax.set_ylabel('Real (V)')
return fig
def transfer_plot(data, fig, error_plot=False):
data.measurements = filter_measurements(
data.measurements, ['pwm_value'], ['Ain'])
title = 'Transfer error plot (%s)' if error_plot else 'Transfer plot (%s)'
title = title % (data.model)
fw = FigureWrapper(
data,
fig,
x='voltage',
y='error (V)' if error_plot else 'voltage',
title=title,
)
vcc = data.vcc
fw.addcol(legend=data.config.pin_in,
x=lambda e: pwm2v(e.pwm_value, vcc),
y=lambda e: an2v(
e.Ain, vcc) - (pwm2v(e.pwm_value, vcc) if error_plot else 0),
)
ax = fw.subplot
if error_plot:
ax.axis([0, 5.1, -0.050, 0.050])
return fig
def transfer_plot(data, fig, error_plot=False):
data.measurements = filter_measurements(data.measurements, ["value"], ["Ain"])
title = "Transfer error plot" if error_plot else "Transfer plot"
title = title
fw = FigureWrapper(data, fig, x="voltage", y="error (V)" if error_plot else "voltage", title=title)
vcc = data.vcc
if error_plot:
fw.subplot.plot([0, vcc], [vcc / 99, vcc / 99], "r-")
fw.subplot.plot([0, vcc], [-vcc / 99, -vcc / 99], "r-")
else:
fw.subplot.plot([0, 0], [vcc, vcc], "r-")
fw.addcol(
legend=data.config.pin_in,
x=lambda e: pot2v(e.value, vcc),
y=lambda e: an2v(e.Ain, vcc) - (pot2v(e.value, vcc) if error_plot else 0),
)
ax = fw.subplot
if error_plot:
ax.axis([0, 5.1, -0.1, 0.1])
return fig
def analog_value_time_plot(data, fig, voltage=False):
fw = FigureWrapper(data,
fig,
x='time',
y='analog_value',
convert2voltage=voltage)
fw.addcol(legend='analog in', y=lambda e: e.Ain)
fw.addcol(legend='digital in', y=lambda e: e.Din * 1023)
return fig
def analog_value_time_plot(data, fig, voltage=False):
fw = FigureWrapper(data,
fig,
x='time',
y='analog_value',
convert2voltage=voltage)
# fw.addcol(legend='rel pwm', y=lambda e: e.pwm_value/255*1023)
fw.addcol(legend='in', y='Ain')
fw.addcol(legend='out', y='Aout')
fw.addcol(legend='amp', y='Aamp')
return fig
def analog_value_time_plot(data, fig, voltage=False):
fw = FigureWrapper(data,
fig,
x='time',
y='analog_value',
convert2voltage=voltage)
# fw.addcol(legend=data.config.pin_in, y='Ain')
# fw.addcol(legend='%s relativ PWM' % data.config.pin_pwm,
# y=lambda e: e.pwm_value / 255 * 1023)
fw.addcol(y='Ain')
fw.addcol(y='pwm_value')
return fig
def io_iv_plot(data, fig):
title = 'Output pin current vs. output voltage (%s)' % (data.model)
extend(data)
fw = FigureWrapper(
data,
fig,
y='voltage',
x='I (mA)',
title=title)
y = 'Vout'
x = 'Iabs'
fw.addcol(legend='high', x=x, y=y,
filter_func=lambda e: e.Dout == 1)
fw.addcol(legend='low', x=x, y=y,
filter_func=lambda e: e.Dout == 0)
return fig
def ohm_invf_plot(data, fig):
d = analyse1(data)
# print d
measurements = d
newdata = dict(measurements=d, project='esr')
# print 676,newdata
fw = FigureWrapper(newdata, fig, x='1/frequency', y='Rx')
# def xtransform(f):
# return 1000000 / (2 * 3.141 * f)
fw.addcol(x=lambda e: 1 / (e.frequency), y='Rx')
ax = fw.subplot
# fmin = filter(lambda e: e['Rx'] is not None, measurements)[0]['frequency']
fmin = min(measurements['frequency'])
# assert 0 ,fmin
ax.set_autoscale_on(False)
# @traced
def Xc(f, c):
return 1 / (2 * np.pi * f * c / 1e6)
ax.plot([0, 1 / (fmin)], [0, Xc(fmin, 0.1)], label='100n')
ax.plot([0, 1 / (fmin)], [0, Xc(fmin, 1)], label='1u')
ax.plot([0, 1 / (fmin)], [0, Xc(fmin, 10)], label='10u')
ax.plot([0, 1 / (fmin)], [0, Xc(fmin, 100)], label='100u')
ax.plot([0, 1 / (fmin)], [0, Xc(fmin, 1000)], label='1000u')
fw.update_legend()
def formatter(x, pos):
if x:
return int(1.0 / x)
else:
return np.inf
ax.xaxis.set_major_formatter(FuncFormatter(formatter))
return fig
