def _update_line_data_fit(self):
if not np.isnan(self.fit_parameters[0]):
self.line_data.set_data(
'fit',
fitting.NLorentzians(*self.fit_parameters)(self.frequency))
p = self.fit_parameters
f = p[1::3]
w = p[2::3]
N = len(p) / 3
contrast = np.empty(N)
c = p[0]
pp = p[1:].reshape((N, 3))
for i, pi in enumerate(pp):
a = pi[2]
g = pi[1]
A = np.abs(a / (np.pi * g))
if a > 0:
contrast[i] = 100 * A / (A + c)
else:
contrast[i] = 100 * A / c
s = ''
for i, fi in enumerate(f):
s += 'f %i: %.6e Hz, HWHM %.3e Hz, contrast %.1f%%\n' % (
i + 1, fi, w[i], contrast[i])
self.line_label.text = s
def _update_line_data_fit(self):
if not np.isnan(self.fit_parameters[0]):
self.line_data.set_data(
'fit',
fitting.NLorentzians(*self.fit_parameters)(self.frequency))
p = self.fit_parameters
f = p[1::3]
w = p[2::3]
c = 100 * p[3::3] / (np.pi * w * p[0])
s = ''
for i, fi in enumerate(f):
s += 'f %i: %.6e Hz, HWHM %.3e Hz, contrast %.1f%%\n' % (
i + 1, fi, w[i], c[i])
self.line_label.text = s