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 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 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 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