Guinier.RgCurveUtils

Guinier.RgCurveUtils#

This module contains functions used to calculate a Rg curve, which is maked of Rg values computed from scattering curves.

compute_rg_curve_from_arrays(D, qv, E, jv=None, progress_cb=None)#

Compute a library-quality RgCurve directly from numpy arrays.

This is the array-level entry point that makes rg_curve computation independent of SSD or SD. It uses the same SimpleGuinier pipeline as compute_rgcurve_info / XrData.compute_rgcurve, but accepts raw arrays instead of an XrData object.

This function is used by BackRunner.run() to compute and export the library rg_curve for LEG-GUI subprocess runs, closing the Guinier_deviation gap between LIB-IN and LEG-GUI without requiring the GUI to construct an SSD.

Parameters:

  • D (ndarray of shape (n_q, n_frames)) – Corrected XR intensity matrix (e.g. from ip_xr_D.npy).

  • qv (ndarray of shape (n_q,)) – q-values in Å⁻¹ (e.g. from ip_xr_qvector.npy).

  • E (ndarray of shape (n_q, n_frames)) – Intensity error matrix (e.g. from ip_xr_E.npy).

  • jv (ndarray of shape (n_frames,) or None) – Original frame numbers. If None, uses np.arange(n_frames).

  • progress_cb (callable or None) – Same signature as in compute_rgcurve_info.

Returns:

Library molass.Guinier.RgCurve.RgCurve object.

Return type:

RgCurve

compute_rgcurve_info(xrdata, progress_cb=None)#

Computes Rg curve information from XR data. It uses the SimpleGuinier class to compute Rg values for each j-curve in the XR data.

Parameters:

  • xrdata (XrData) – The XR data from which to compute the Rg curve information.

  • progress_cb (callable or None, optional) – Optional callback called after each frame with (rg_buffer, j) where rg_buffer is a float array of shape (n_frames,) containing the Rg values computed so far (0 for not-yet-computed frames) and j is the 0-based column index of the current frame. The signature matches the legacy ProgressCallback so GUI callers can drive a progress bar and live Rg overlay with no additional adaptation.

Returns:

rginfo_list – A list of tuples where each tuple contains (index, SimpleGuinier result).

Return type:

list of tuples

class ValidBools(all_frames, segment)#

Bases: tuple

Create new instance of ValidBools(all_frames, segment)

all_frames#

Alias for field number 0

segment#

Alias for field number 1

convert_to_milder_qualities(qualities)#

Raise the quality floor so that low-quality frames still get some weight.

Maps raw qualities (0–1) to a compressed range (VALID_BASE_QUALITY–1):

out[i] = 0.3 + 0.7 * qualities[i] for qualities[i] > 0.01

Deprecated since version No: longer used for Guinier_deviation weights (see molass-legacy issue #11). Raw qualities are now used directly in GuinierDeviation. Kept for backward compatibility (e.g. max_mask threshold).

get_connected_curve_info(rg_curve, debug=False)#

Extract concatenated x, y, Rg, and quality arrays from a segmented Rg curve.

Works with any object that exposes the segmented Rg interface: get_curve_segments(), .qualities, .states, .slices, .x. This covers RgProcess.RgCurve, RgProcess.RgCurveProxy, and Bridge.LegacyRgCurve.

Returns:

  • x_ (ndarray) – Concatenated frame positions of all active segments.

  • y_ (ndarray) – Corresponding elution intensities.

  • rgv (ndarray) – Corresponding smoothed Rg values.

  • qualities (ndarray) – Concatenated raw Guinier quality scores (one per active frame).

  • valid_bools (ValidBools) – Named-tuple with two boolean masks: all_frames (len = len(rg_curve.x)) and segment (len = len(qualities)).

get_reconstructed_curve(size, valid_bools, Cxr, rg_params)#

Reconstruct the weighted-average Rg curve from component elution curves.

Parameters:

  • size (int) – Length of the output array (number of active frames in the segment).

  • valid_bools (ValidBools)

  • Cxr (ndarray, shape (n_components, n_all_frames))

  • rg_params (sequence of float)

Returns:

rrgv

Return type:

ndarray, shape (size,)

compute_rg_curves(x, xr_weights, rg_params, xr_cy_list, xr_ty, rg_curve, debug=False)#

Compute observed and reconstructed Rg curves for each active segment.

Returns:

  • rg_curves1 (list of (x, rg) tuples — observed Rg from rg_curve.segments)

  • rg_curves2 (list of (x, rg) tuples — model-reconstructed Rg)

plot_rg_curves(ax, xrh_params, rg_params, x, xr_cy_list, xr_ty, rg_curve)#

Plot observed and reconstructed Rg curves on ax (a matplotlib Axes).

Used by the legacy model-parameter plot utilities (EghPlotUtils, etc.).

compute_rgcurve_info_atsas(xrdata)#

Computes Rg curve information from XR data using ATSAS autorg. It uses the AutorgRunner class to compute Rg values for each j-curve in the XR data.

Parameters:

xrdata (XrData) – The XR data from which to compute the Rg curve information.

Returns:

rginfo_list – A list of tuples where each tuple contains (index, ATSAS Autorg result).

Return type:

list of tuples