def fit_energy_dependence(
data, envir, curve_loader, db_conn, constrained_background=False, retries=10, rms_filter=True
):
for s, t, w, pp, z, bg in zip(
data.Timestamp.values, data.temperature_start.values, data.W.values, data.PP, data.Z.values, data.BG.values
):
curve = curve_loader(s)
for i in range(0, retries):
result = update_hanle(
data=curve,
temperature=t * U_.kelvin,
wavelength=w * U_.nanometer,
probe_intensity=pp * U_.watt,
mbr_brf_displacement=z * U_.millimeter,
probe_background=bg * U_.radian,
constrain_background=False,
rms_filter=rms_filter,
db_conn=db_conn,
**expand_kwargs(update_hanle, envir)
)
print(result)
if result is not None:
print("Found better fit, updating db")
else:
print("Fit not updated")
def fit_power_dependence(data, envir, curve_loader, db_conn, constrained_background=False, retries=10, rms_filter=True):
for s, t, w, pup in zip(data.Timestamp.values, data.temperature_start.values, data.W.values, data.PuP):
curve = curve_loader(s)
for i in range(0, retries):
result = update_hanle(
data=curve,
temperature=t * U_.kelvin,
wavelength=w * U_.nanometer,
pump_intensity=pup * U_.watts,
constrain_background=False,
rms_filter=rms_filter,
db_conn=db_conn,
**expand_kwargs(update_hanle, envir)
)
print(result)
if result is not None:
print("Found better fit, updating db")
else:
print("Fit not updated")