def test_iplanck(self):
"""
Check that iBlambda(lmbda, Blambda(lmbda, x)) = x
"""
Flux = rad.planck(lmbda * 1.0e9, Te_eV, 'lambda')
Flux = Flux * 1.0e-9 #to W.m⁻².sr⁻¹.nm⁻¹
Tout = rad.iplanck(lmbda * 1.0e9, Flux)
assert_allclose(Tout, Te_eV)
def test_iplanck(self):
"""
Check that iBlambda(lmbda, Blambda(lmbda, x)) = x
"""
Flux = rad.planck(lmbda*1.0e9, Te_eV, 'lambda')
Flux = Flux*1.0e-9 #to W.m⁻².sr⁻¹.nm⁻¹
Tout = rad.iplanck(lmbda*1.0e9, Flux)
assert_allclose(Tout, Te_eV)
def se_calibration(counts,
lmbda,
F,
transmission,
detectorsize,
method='explicit',
out='tele',
diag='sop',
**args):
"""
Compute the calibration for a streaked self emission system.
This function calculates the number of electrons ejected by the
photocathode in a SOP configuration.
Parameters:
-----------
General:
--------
- lmbda [ndarray]: wavelenght (nm) array
- F [float]: F number of the first lens
- transmission [ndarray]: Total transmission of the optical system, including the
filter (same shape as the nu)
- detectorsize [float] Size of a pixel in spatial direction in μm
- method [str]: method to use
Streak only parameters:
----------------------
- slitwidth [float] Size of the slit in px
- sweepspeed Sweep speed of the streak [100ns, 50ns, etc] in pixel/ns
GOI relative:
-------------
Returns:
--------
- Flux or tele[eV], Flux_norm [float]: photon flux (W.m⁻².sr⁻¹.nm⁻¹.counts⁻¹)
"""
args = locals()
args.update(args['args'])
if method not in ['implicit', 'explicit'] or\
out not in ['tele', 'flux'] or\
diag not in ['sop', 'goi']:
raise ValueError('Wrong input arguments!')
# deleting all the arguments we don't want to pass
for key in ['counts', 'out', 'diag', 'args']:
del args[key]
cal_function = {'sop': _sop_calibration, 'goi': _se_calibration_goi}[diag]
if method == 'explicit':
Flux = cal_function(**args)
if out == 'flux':
return Flux * counts
elif out == 'tele':
max_idx = np.argmax(transmission)
lmbda_max = lmbda[max_idx]
return iplanck(lmbda_max, counts * Flux)
elif method == "implicit":
tele_max = np.array([0.1]) # staring temperature at 0.1 eV
counts_max = 0
# Upper bound for the temperature we would need to go to
while counts_max < counts.max():
tele_max *= 2
counts_max = cal_function(tele=tele_max, **args)[0]
tele_i = np.linspace(0, tele_max, 1000)
counts_i = cal_function(tele=tele_i, **args)
calibration_fit = interp1d(counts_i,
tele_i,
bounds_error=False,
fill_value=0)
return calibration_fit(counts)
def se_calibration(counts, lmbda, F, transmission, detectorsize, method="explicit", out="tele", diag="sop", **args):
"""
Compute the calibration for a streaked self emission system.
This function calculates the number of electrons ejected by the
photocathode in a SOP configuration.
Parameters:
-----------
General:
--------
- lmbda [ndarray]: wavelenght (nm) array
- F [float]: F number of the first lens
- transmission [ndarray]: Total transmission of the optical system, including the
filter (same shape as the nu)
- detectorsize [float] Size of a pixel in spatial direction in μm
- method [str]: method to use
Streak only parameters:
----------------------
- slitwidth [float] Size of the slit in px
- sweepspeed Sweep speed of the streak [100ns, 50ns, etc] in pixel/ns
GOI relative:
-------------
Returns:
--------
- Flux or tele[eV], Flux_norm [float]: photon flux (W.m⁻².sr⁻¹.nm⁻¹.counts⁻¹)
"""
args = locals()
args.update(args["args"])
if method not in ["implicit", "explicit"] or out not in ["tele", "flux"] or diag not in ["sop", "goi"]:
raise ValueError("Wrong input arguments!")
# deleting all the arguments we don't want to pass
for key in ["counts", "out", "diag", "args"]:
del args[key]
cal_function = {"sop": _sop_calibration, "goi": _se_calibration_goi}[diag]
if method == "explicit":
Flux = cal_function(**args)
if out == "flux":
return Flux * counts
elif out == "tele":
max_idx = np.argmax(transmission)
lmbda_max = lmbda[max_idx]
return iplanck(lmbda_max, counts * Flux)
elif method == "implicit":
tele_max = np.array([0.1]) # staring temperature at 0.1 eV
counts_max = 0
# Upper bound for the temperature we would need to go to
while counts_max < counts.max():
tele_max *= 2
counts_max = cal_function(tele=tele_max, **args)[0]
tele_i = np.linspace(0, tele_max, 1000)
counts_i = cal_function(tele=tele_i, **args)
calibration_fit = interp1d(counts_i, tele_i, bounds_error=False, fill_value=0)
return calibration_fit(counts)
