def test_specfit(rawdata, noise, error, params):
for i in range(100):
passed = True
parameter_noise = [
params[0] + abs(np.random.randn()) * parameter_error_amplitude[0],
params[1] + abs(np.random.randn()) * parameter_error_amplitude[1],
params[2] + abs(np.random.randn()) * parameter_error_amplitude[2]
]
guesses = np.array(params) + parameter_noise
sp = Spectrum(xarr=xarr, data=rawdata + noise, error=error)
# sp.plotter(axis=plt.gca(), errstyle='fill')
sp.specfit(guesses=guesses)
assertion = ((np.array(sp.specfit.fitter.mpp) - np.array(params)) /
parameter_noise)**2
print('(mpp - params / param_noise )^2 = ', assertion)
for j, result in enumerate(assertion):
if strict_assertion:
assert result < 2
if result >= 2:
passed = False
continue
if passed:
for j in range(3):
passes['passes'][j] += 1
passes['avg_difference'][j] += abs(sp.specfit.fitter.mpp[j] -
params[j])
else:
for j in range(3):
fails['fails'][j] += 1
fails['avg_difference'][j] += abs(sp.specfit.fitter.mpp[j] -
params[j])
# plt.show()
for i, j in enumerate(passes['avg_difference']):
if passes['passes'][i]:
passes['avg_difference'][i] = j / passes['passes'][i]
for i, j in enumerate(fails['avg_difference']):
if fails['fails'][i]:
fails['avg_difference'][i] = j / fails['fails'][i]
print('passes:', passes)
print('fails:', fails)
def test_specfit(rawdata, noise, error, params):
for i in range(100):
passed = True
parameter_noise = [
params[0] + abs(np.random.randn()) * parameter_error_amplitude[0],
params[1] + abs(np.random.randn()) * parameter_error_amplitude[1],
params[2] + abs(np.random.randn()) * parameter_error_amplitude[2],
]
guesses = np.array(params) + parameter_noise
sp = Spectrum(xarr=xarr, data=rawdata + noise, error=error)
# sp.plotter(axis=plt.gca(), errstyle='fill')
sp.specfit(guesses=guesses)
assertion = ((np.array(sp.specfit.fitter.mpp) - np.array(params)) / parameter_noise) ** 2
print("(mpp - params / param_noise )^2 = ", assertion)
for j, result in enumerate(assertion):
if strict_assertion:
assert result < 2
if result >= 2:
passed = False
continue
if passed:
for j in range(3):
passes["passes"][j] += 1
passes["avg_difference"][j] += abs(sp.specfit.fitter.mpp[j] - params[j])
else:
for j in range(3):
fails["fails"][j] += 1
fails["avg_difference"][j] += abs(sp.specfit.fitter.mpp[j] - params[j])
# plt.show()
for i, j in enumerate(passes["avg_difference"]):
if passes["passes"][i]:
passes["avg_difference"][i] = j / passes["passes"][i]
for i, j in enumerate(fails["avg_difference"]):
if fails["fails"][i]:
fails["avg_difference"][i] = j / fails["fails"][i]
print("passes:", passes)
print("fails:", fails)
