simulate op• Data kinds: कोई नहीं → sweep (केवल arguments से तय होने वाला op — यह कोई image या data input नहीं लेता)
• Call: import fullseye as fs; fs.ledger.csi_signal_simulate(surface_um=6.0, z_start_um=0.0, z_step_um=0.05, n_planes=241, wavelength_um=0.6, envelope_fwhm_um=2.8, envelope_sigma_um=None, bias=0.5, amplitude=0.4, reflectivity=1.0, noise=0.0, seed=0) (implementation को सीधे call करना हो तो import interferometry; interferometry.csi_signal_simulate(surface_um=6.0, z_start_um=0.0, z_step_um=0.05, n_planes=241, wavelength_um=0.6, envelope_fwhm_um=2.8, envelope_sigma_um=None, bias=0.5, amplitude=0.4, reflectivity=1.0, noise=0.0, seed=0), registry से लेना हो तो opsinterferometry.get("csi_signal_simulate"))
ज्ञात surface height पर एक pixel का z-scan interferogram synthesise करता है।
> नीचे का विस्तृत विवरण मूल text में है — सारांश और headings का अनुवाद हो चुका है।
The coherence-scanning forward model, and the reason every other operator here has an exact answer to be checked against::
I(z) = bias + amplitude*reflectivity * exp(-(z-z0)^2 / 2 sigma^2)
• cos(4*pi*(z-z0)/wavelength)
with z0 = surface_um. The 4 is the double pass — light goes down to the surface and back, so one fringe is wavelength/2 of *height*, not a whole wavelength. Getting that factor wrong is a clean 2x in every height this module produces, which is why it is written out here rather than hidden in a constant.
surface_um: the true surface height z0, in the scan's own
coordinate. Need not land on a scan plane — the
sub-step case is the interesting one and the tests use
it deliberately.
z_start_um/z_step_um/n_planes: the scan grid,
z_k = z_start_um + k*z_step_um.
wavelength_um: mean wavelength of the source.
envelope_fwhm_um: the FWHM of the envelope along the scan axis. Give
this *or* envelope_sigma_um, never both. It is
half the source coherence length, because the
double pass makes OPD = 2z;
csi_design returns both under separate names
for exactly that reason.
bias/amplitude: the intensity pedestal a and fringe amplitude b.
reflectivity: per-pixel scale on the fringe amplitude (>= 0). It
scales the envelope and therefore
csi_contrast_map, and — this is the honest part
— it does not move the envelope peak, so it does not
bias csi_peak_position. A *spatially varying*
reflectivity biases nothing either; what does bias the
centroid is where the peak sits in the window, and that
is documented on csi_peak_position.
noise: additive Gaussian sigma (0 = the exact model).
seed: integer seed for that noise (no None).
Returns a 1-D float64 array of n_planes intensities.
Ground truth: with noise=0 and the surface centred in the scan, the "gaussian" estimator of csi_peak_position returns *surface_um* to 1.43e-07 um over sub-step offsets, and to 2.9e-14 um when the envelope is given analytically instead of through the Hilbert transform (both pinned in the tests).
Raises ValueError: a non-real / non-finite / string / bool parameter, a non-positive z_step_um / wavelength_um / envelope width, a negative bias / amplitude / reflectivity / noise, n_planes outside [3, MAX_SCAN_POINTS], a z_step_um at or past the wavelength_um/4 Nyquist ceiling, and a *surface_um* outside the scan range (which is the case a real instrument reports as "no surface found", not as a height).
• coherence_scanning family guide
• Sample data catalog (DL URL / license) — 2-D के लिए skimage.data (BSD/public) + synthetic, 3-D के लिए real data sources (Stanford/PDS आदि) के DL URL।
• Operators का स्रोत और संदर्भ — इस op family के मूल research/methods के स्रोत।
• Algorithm का मानक स्रोत (लेखक, वर्ष) और उपयोग ऊपर की family usage guide में दिए गए हैं।
• coherence_scanning — py -3.11 examples/coherence_scanning.py
sweep को input के रूप में लेते हैं)csi_envelope · csi_peak_position · chromatic_confocal_height
simulate)csi_stack_simulate · chromatic_confocal_simulate
*Provenance: interferometry.py — INTERFEROMETRY operator registry. यह per-op note tools/opdocs.py md से अपने-आप generate होता है (हाथ से edit न करें)।*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.