def main():
io = Io()
io.eval_args()
args = sys.argv
fail = False
ret = {'ok': True}
unit = 'Pa'
cmc = False
if '--ids' in args:
idx_ids = args.index('--ids') + 1
try:
ids = args[idx_ids].split('@')
except:
fail = True
if not fail and len(ids) > 0:
for id in ids:
doc = io.get_doc_db(id)
customer_object = doc.get('Calibration').get('CustomerObject')
if customer_object.get("Class") == "SRG":
customer_device = Srg(doc, customer_object)
if customer_object.get("Class") == "CDG":
customer_device = Cdg(doc, customer_object)
tdo = ToDo(doc)
analysis = doc.get('Calibration').get('Analysis')
if "Values" in analysis and "Uncertainty" in analysis["Values"]:
del analysis["Values"]["Uncertainty"]
ana = Analysis(doc, init_dict=analysis)
se2_uncert = UncertSe2(doc)
result_type = analysis.get("AnalysisType", "default")
result_type = "se2_expansion_direct"
res = Result(doc, result_type=result_type)
p_cal = ana.pick('Pressure', 'cal', unit)
p_ind_corr = ana.pick('Pressure', 'ind_corr', unit)
p_off = ana.pick('Pressure', 'offset', unit)
conv = res.Const.get_conv(from_unit=unit,
to_unit=res.ToDo.pressure_unit)
average_index = res.ToDo.make_average_index(
p_cal * conv, res.ToDo.pressure_unit)
print(average_index)
average_index = ana.coarse_error_filtering(
average_index=average_index)
print(average_index)
average_index, ref_mean, ref_std, loops = ana.fine_error_filtering(
average_index=average_index)
pressure_range_index = ana.make_pressure_range_index(
ana, average_index)
print(average_index)
print(ref_mean)
print(ref_std)
print(loops)
if result_type == "se2_expansion_direct" and tdo.type == "error":
average_index, reject_index = ana.ask_for_reject(
average_index=average_index)
reject_index_offset = ana.ask_for_reject_offset(
average_index=average_index)
d = {
"AverageIndex": average_index,
"AverageIndexFlat": ana.flatten(average_index),
"PressureRangeIndex": pressure_range_index,
"RejectIndex": reject_index,
"RejectIndexOffset": reject_index_offset
}
p_tdo, p_tdo_unit = tdo.Pres.get_value_and_unit("target")
conv = res.Const.get_conv(from_unit=p_tdo_unit, to_unit="Pa")
p_tdo = conv * p_tdo
#assuming pascals, temperature correction only if more than 1 decade below 100 Pa
p_tdo_evis = [
p_tdo[i] for i in range(len(p_tdo)) if p_tdo[i] < 9.5
]
if len(p_tdo_evis) > 1:
e_vis, cf_vis, u_vis, vis_unit = ana.ask_for_evis()
d["Evis"] = e_vis
d["CFvis"] = cf_vis
d["Uvis"] = u_vis
d["VisUnit"] = vis_unit
print(d)
ana.store_dict(quant="AuxValues", d=d, dest=None, plain=True)
res.store_dict(quant="AuxValues", d=d, dest=None, plain=True)
if "Uncertainty" in customer_object:
print("lll")
u_dev = customer_device.get_total_uncert(
meas_vec=p_ind_corr,
meas_unit="Pa",
return_unit="Pa",
res=ana,
skip_source="standard",
prefix=False)
se2_uncert.u_PTB_rel(ana)
se2_uncert.make_offset_stability(ana)
customer_device.repeat_uncert(ana)
customer_device.device_uncert(ana)
ana.total_uncert()
u = ana.pick("Uncertainty", "total_rel", "1")
print(customer_device.doc)
print("ffffffffffffffffffffffffffffff")
print(tdo.type)
print(result_type)
if result_type == "se2_expansion_direct" and tdo.type == "sigma":
p_ind_corr = np.take(p_ind_corr, ana.flatten(average_index))
p_cal = np.take(p_cal, ana.flatten(average_index))
p_off = np.take(p_off, ana.flatten(average_index))
d = {
"AverageIndex": average_index,
"AverageIndexFlat": ana.flatten(average_index)
}
print(p_ind_corr)
print(p_cal)
#u = np.delete(u, skip)
sigma_null, sigma_slope, sigma_std = customer_device.sigma_null(
p_cal=p_cal,
cal_unit=unit,
p_ind=p_ind_corr,
ind_unit=unit)
d["SigmaNull"] = sigma_null
d["SigmaCorrSlope"] = np.abs(sigma_slope / sigma_null)
d["SigmaStd"] = sigma_std
# aux_values_pres = Values(doc.get('Calibration').get('Measurement').get("AuxValues").get("Pressure"))
# rd, rd_unit = aux_values_pres.get_value_and_unit(d_type="offset")
# d["OffsetMean"] = np.nanmean(rd)
# d["OffsetStd"] = np.nanstd(rd)
# d["OffsetUnit"] = rd_unit
ana.store_dict(quant="AuxValues", d=d, dest=None, plain=True)
res.store_dict(quant="AuxValues", d=d, dest=None, plain=True)
maesurement_date = cl.Counter(
doc["Calibration"]["Measurement"]["Values"]["Date"]
["Value"]).most_common(1)[0][0]
doc["Calibration"]["Measurement"]["Date"] = [{
"Type":
"measurement",
"Value": [maesurement_date]
}]
res.make_measurement_data_section(ana, result_type=result_type)
if tdo.type == "error":
# start build cert table
p_ind, err, u = res.make_error_table(ana,
pressure_unit=unit,
error_unit='1')
doc = ana.build_doc("Analysis", doc)
doc = res.build_doc("Result", doc)
io.save_doc(doc)
else:
ret = {"error": "no --ids found"}
def main():
io = Io()
io.eval_args()
ret = {"ok": True}
result_type = "sens"
i_unit = "A"
for id in io.ids:
doc = io.get_doc_db(id)
tdo = ToDo(doc)
if tdo.type not in ["sens"]:
sys.exit("wrong script")
if tdo.type == "sens":
result_type = "sens"
display = Display(doc)
cus_dev = init_customer_device(doc)
analysis = doc.get("Calibration").get("Analysis")
## wrong type:
del analysis["Values"]["Sensitivity"]
ana = Analysis(doc, init_dict=analysis, analysis_type=result_type)
res = Result(doc, result_type=result_type, skip=io.skip)
## conversion to ana.pressure_unit if necessary
cal_dict = ana.pick_dict("Pressure", "cal")
p_ind_corr = ana.pick("Pressure", "ind_corr", i_unit)
p_ind = ana.pick("Pressure", "ind", i_unit)
p_ind_offset = ana.pick("Pressure", "ind_offset", i_unit)
if cal_dict.get("Unit") != ana.pressure_unit:
p_cal = ana.pick("Pressure", "cal", tdo.pressure_unit)
conv = ana.Const.get_conv(from_unit=tdo.pressure_unit,
to_unit=ana.pressure_unit)
p_cal = p_cal * conv
else:
p_cal = ana.pick("Pressure", "cal", ana.pressure_unit)
T_gas = ana.pick("Temperature", "Tuhv", "K")
T_room = ana.pick("Temperature", "Troom", "K")
if T_room is None:
T_room = T_gas
u_std = ana.pick("Uncertainty", "uncertPcal_rel", "1")
## recal Sensitivity
s = p_ind_corr / (cus_dev.emis_current(i_unit) * p_cal)
ana.store("Pressure", "cal", p_cal, ana.pressure_unit)
ana.store("Pressure", "offset", p_ind_offset, i_unit)
ana.store("Sensitivity", "gauge", s, "1/{}".format(ana.pressure_unit))
ana.store("Uncertainty", "standard", u_std, "1")
ana.store("Temperature", "gas", T_gas, "K")
ana.store("Temperature", "room", T_room, "K")
conv = ana.Const.get_conv(from_unit=ana.pressure_unit,
to_unit=tdo.pressure_unit)
average_index = tdo.make_average_index(p_cal * conv,
tdo.pressure_unit,
max_dev=0.2)
## will be filled up with aux values:
d = {}
display.check_outlier_sens(ana)
average_index, reject_index = ana.ask_for_reject(
average_index=average_index)
flat_average_index = ana.flatten(average_index)
if result_type == "sens":
T, Tu = ana.ask_for_bake_out_temperature()
if T is not None:
d["Bakeout"] = True
d["BakeoutTemperature"] = float(T)
d["BakeoutTemperatureUnit"] = Tu
t, tu = ana.ask_for_bake_out_time()
d["BakeoutTime"] = float(t)
d["BakeoutTimeUnit"] = tu
else:
d["Bakeout"] = False
p, pu, t, tu = ana.ask_for_sputter()
if T is not None:
d["Sputter"] = True
d["SputterPressure"] = float(p)
d["SputterPressureUnit"] = pu
d["SputterTime"] = float(t)
d["SputterTimeUnit"] = tu
else:
d["Sputter"] = False
d["AverageIndex"] = average_index
d["AverageIndexFlat"] = flat_average_index
ana.store_dict(quant="AuxValues", d=d, dest=None)
## rm values
p_cal = np.take(p_cal, flat_average_index)
p_ind_corr = np.take(p_ind_corr, flat_average_index)
s = np.take(s, flat_average_index)
## store reduced quant. for plot
ana.store("Pressure",
"red_ind_corr",
p_ind_corr,
i_unit,
dest="AuxValues")
ana.store("Pressure",
"red_cal",
p_cal,
ana.pressure_unit,
dest="AuxValues")
ana.store("Sensitivity",
"red_gauge",
s,
"1/{}".format(ana.pressure_unit),
dest="AuxValues")
## offset contrib
cus_dev.coll_uncert(ana, ind_unit=i_unit)
## default uncert. contrib. repeat
cus_dev.repeat_uncert(ana, ind_unit=i_unit)
cus_dev.digit_uncert(ana, ind_unit=i_unit)
cus_dev.emis_uncert(ana, ind_unit=i_unit)
cus_dev.device_uncert(ana)
## the uncertainty of the standard is
# already calculated at analysis step
ana.total_uncert()
## store red version for plot
u_rep = ana.pick("Uncertainty", "repeat", "1")
u_off = ana.pick("Uncertainty", "offset", "1")
u_tot = ana.pick("Uncertainty", "total_rel", "1")
u_dev = ana.pick("Uncertainty", "device", "1")
u_std = ana.pick("Uncertainty", "standard", "1")
ana.store("Uncertainty",
"red_u_rep",
np.take(u_rep, flat_average_index),
"1",
dest="AuxValues")
ana.store("Uncertainty",
"red_u_std",
np.take(u_std, flat_average_index),
"1",
dest="AuxValues")
ana.store("Uncertainty",
"red_u_dev",
np.take(u_dev, flat_average_index),
"1",
dest="AuxValues")
ana.store("Uncertainty",
"red_u_tot",
np.take(u_tot, flat_average_index),
"1",
dest="AuxValues")
ana.store("Uncertainty",
"red_u_off",
np.take(u_off, flat_average_index),
"1",
dest="AuxValues")
display.plot_uncert(ana)
# start making data sections
res.make_measurement_data_section(ana, result_type=result_type)
# start build cert table
p_cal_mv, p_ind_mv, s_mv, u_mv = res.make_sens_table(
ana,
pressure_unit=ana.pressure_unit,
sens_unit='1/Pa',
uncert_unit="1",
ind_unit="A")
ana.store("Pressure", "ind_mean", p_ind_mv, i_unit, dest="AuxValues")
ana.store("Pressure",
"cal_mean",
p_cal_mv,
ana.pressure_unit,
dest="AuxValues")
ana.store("Sensitivity",
"gauge_mean",
s_mv,
"1/{}".format(ana.pressure_unit),
dest="AuxValues")
ana.store("Uncertainty", "total_mean", u_mv, "1", dest="AuxValues")
display.plot_mean(ana)
doc = ana.build_doc("Analysis", doc)
doc = res.build_doc("Result", doc)
io.save_doc(doc)