Configuration Reference

This page lists every parameter of the LLWP configuration, together with its type, default value and the values it accepts. The configuration itself can be inspected and changed from within LLWP under View > Config (or Preferences on Mac); see the Configuration section of the docs for how loading, saving and the .ini file work. Parameters whose type is dict or list are entered as JSON in the configuration window.

Parameter Type Default Allowed values & description
Plotting — Controls the layout, scaling and appearance of the main Loomis-Wood plot grid. Most of these are also exposed directly as toolbar controls, see Navigating the Plots, or via the Scaling window for the y-axis settings.
plot_dpi int 100 Resolution (dots per inch) of the plotted figures. Applies to the main plot, ASAP and the various module plots (Blended Lines, Residuals, Peakfinder, …).
plot_width float 20 Width of each subplot's x-range (in frequency units, e.g. MHz), centered on the reference position plus plot_offset. Same as the Width toolbar field. Overridden per-cell if plot_widthexpression is set.
plot_offset float 0 Shift of a subplot's window center relative to its reference (series) position, in frequency units. Set via Plot > Set Offset. Overridden per-cell if plot_offsetexpression is set.
plot_offsetisrelative bool True Whether the value typed into the Set Offset dialog is interpreted as relative to the reference position (True) or as an absolute frequency (False). plot_offset itself is always stored relative internally.
plot_rows int 5 Number of subplot rows in the main plot grid (≥ 1). Changing it rebuilds the plot grid.
plot_cols int 1 Number of subplot columns (≥ 1); each column corresponds to one Reference Series tab.
plot_linmarker str "*" Matplotlib marker style used to mark assigned (*.lin) line positions on the plots, e.g. "*", "o", "x".
plot_widthexpression str "" Optional Python expression to make the subplot width vary per cell. Evaluated with numpy-array variables x (reference position), w (the plain plot_width value), i_row, i_col, and the quantum numbers qnu1…qnuN/qnl1…qnlN (N = series_qns). Empty string disables it. Set via the Width dialog's expression mode.
plot_offsetexpression str "" Same mechanism as plot_widthexpression but for the offset, with o standing in for the plain plot_offset value. Set via the Offset dialog's expression mode.
plot_yscale str "Per Plot" How the y-axis range and the cat/prediction scaling are determined. One of "Per Plot" (cat intensities scaled so their max matches the visible experimental max; y-range follows the visible experimental data), "Global" (cat scaled by plot_expcat_factor * 10**plot_expcat_exponent; y-range follows the whole loaded experimental spectrum) or "Custom" (same cat scaling as Global, but the y-range is fixed to plot_yscale_min/plot_yscale_max).
plot_expcat_factor float 1 Linear multiplier for cat/prediction intensities, used together with plot_expcat_exponent when plot_yscale is "Global" or "Custom". Same as the y-Exp/y-Cat field.
plot_expcat_exponent int 10 Power-of-ten exponent paired with plot_expcat_factor (effective factor is factor · 10^exponent).
plot_yscale_min float -100 Fixed lower y-axis bound, only used when plot_yscale is "Custom".
plot_yscale_max float 300 Fixed upper y-axis bound, only used when plot_yscale is "Custom".
plot_ymargin float 0.1 Fractional margin added above and below the computed y-range (e.g. 0.1 = 10%), applied regardless of the plot_yscale mode.
plot_xticks int 3 Number of x-axis tick positions per subplot, evenly spaced across its visible range.
plot_xtickformat str "offset" How x-tick labels are formatted. "absolute" shows the raw frequency; "scientific" uses trimmed scientific notation (e.g. 1.23e5); any other value (including the default "offset") shows ticks relative to the subplot's reference position.
plot_gridspeckwargs dict {"hspace": 0, "wspace": 0} Extra keyword arguments forwarded to matplotlib's GridSpec (via Figure.subplots(gridspec_kw=...)), e.g. hspace, wspace, left, right, height_ratios.
plot_fontdict dict {"size": 10} Keyword arguments forwarded to matplotlib's rc("font", **kwargs) to control the default plot font, e.g. size, family, weight.
plot_bins int 4000 Target number of bins used to downsample dense exp/cat data for display, once the visible data exceeds plot_skipbinning points.
plot_skipbinning int 1000 Minimum number of visible data points required before binning kicks in — datasets with fewer points are always rendered at full resolution.
plot_hovercutoff float 20 Half-width (in frequency units) of the window around the mouse cursor used to look up nearby transitions for the Close-By-Lines window.
plot_annotationkwargs dict {"x": 1, "y": 1, "horizontalalignment": "right", "verticalalignment": "top"} Keyword arguments forwarded to matplotlib's text placement call for each subplot's quantum-number annotation (position in axes-fraction coordinates, alignment, font size, …).
plot_annotationfstring str "{qns}" Python str.format() template for each subplot's annotation text. Available fields: qns (formatted upper ← lower quantum-number string), x (reference position), width (subplot width), and the individual quantum numbers qnu1…/qnl1…. Empty string disables the annotation.
Convolution — Applies an optional lineshape convolution to the simulated (cat) spectrum before it is drawn, useful to mimic experimental line broadening. See the Convolution feature page for a walkthrough of the Sticks to Lineshape window.
convolution_function str "Off" Selects the convolution lineshape. One of "Off" (no convolution), "Gauss", "Lorentz", "Voigt" (combines both widths), or "Custom" (kernel entered directly as comma-separated numbers instead of generated from the width settings).
convolution_widthgauss float 1 Gaussian width parameter, used when convolution_function is "Gauss" or "Voigt".
convolution_widthlorentz float 1 Lorentzian width parameter, used when convolution_function is "Lorentz" or "Voigt".
convolution_stepwidth float 0.2 Frequency step used both to bin the cat spectrum before convolving and to space the generated kernel's sample points.
convolution_kernelwidth float 2 Total width (in frequency units) of the generated Gauss/Lorentz/Voigt kernel; not used for "Off"/"Custom".
convolution_derivative int 0 Derivative order of the lineshape used to build the kernel: 0 (plain lineshape), 1 or 2 (1st/2nd derivative, for derivative spectroscopy).
convolution_amplitude float 1 Amplitude scaling factor applied when generating the Gauss/Lorentz/Voigt kernel.
convolution_kernel list [] The actual discrete convolution kernel (list of floats) applied to the binned cat spectrum. Normally computed automatically from the settings above; only edit directly when using "Custom" mode.
Reference Series — Settings for the Reference Series tabs, quantum-number handling and blend detection.
series_qns int 4 Number of active quantum numbers (upper/lower) used throughout the program — series definitions, tables, blend queries, etc. Auto-detected from loaded *.cat files, or set manually. Valid range is 1 up to the compiled-in maximum (10 by default, configurable only via the LLWP_QNS environment variable).
series_currenttab int 0 Index of the currently active tab in the Reference Series dock.
series_references list [] Internal, serialized state of every Reference Series tab (method, quantum numbers, list data, expression, …) — one entry per tab. Not intended for manual editing; restored automatically on startup.
series_blendwidth float 0 Half-width (in frequency units) around a fitted line's predicted position within which nearby cat predictions are searched for potential blended (overlapping) transitions. 0 disables blend checking.
series_blendquery str "" Optional pandas query expression: if all nearby cat entries found within series_blendwidth satisfy it, they are auto-assigned as a weighted blend without opening the interactive Blend dialog. Empty string always shows the dialog.
series_blendminrelratio float 0 Minimum intensity ratio (relative to the matched transition's predicted intensity) a nearby cat line must reach to be considered part of a blend. 0 disables the filter.
series_showqnsactions bool True Shows/hides the row of custom quick-action buttons (see series_changeqnsactions) at the bottom of the Reference Series selector.
series_changeqnsactions dict {} User-defined quick-nudge buttons for the "Transition" series method. Maps a button label to a two-element list of integer deltas [upper_deltas, lower_deltas] (one delta per active quantum number) applied to the current quantum numbers when clicked, e.g. {"Next Ka": [[0, 1, -1], [0, 1, -1]]}.
series_expressionkwargs dict {} Extra named constants merged into the evaluation namespace of the "Expression" series method, alongside the built-in N and N0, e.g. {"B": 4000} lets you write (N+N0)*B*2.
Fitting — Settings for fitting a selected range of the spectrum to a line position, see Assigning Lines.
fit_fitmethod str "Pgopher" Fit algorithm used to determine a line's exact frequency from the selected data points. One of "Pgopher" (intensity-weighted centroid above the half-max cutoff, no true fit), "Polynom" (fixed-rank polynomial fit, see fit_polynomrank), "MultiPolynom" (best of several polynomial ranks up to fit_polynommaxrank), or a lineshape fit: "Gauss", "Lorentz", "Voigt", and their "… 1st Derivative"/"… 2nd Derivative" variants. Selectable under Fit > Choose Fit Function; ASAP offers a reduced subset (Pgopher, Polynom, MultiPolynom, Gauss, Lorentz).
fit_uncertainty_method str "Value" How the uncertainty of a newly-fitted assignment is determined. One of "Fit" (the fit routine's own statistical uncertainty — currently always 0 for all built-in fit methods), "Obs-Calc" (absolute difference between the fitted and the reference/predicted position), or "Value" (the fixed fit_uncertainty value).
fit_uncertainty float 0.05 Fixed uncertainty assigned to new lines when fit_uncertainty_method is "Value". Same as the Default Uncertainty field.
fit_peakdirection int 1 Constrains which peak direction the fit routines search for: positive values restrict to positive-going peaks (the default), negative values to negative-going peaks (dips), and 0 allows both. Shared by the main fit tool, ASAP and Blended Lines.
fit_offset bool True Whether lineshape fits (Gauss/Lorentz/Voigt and derivatives) include an additional fitted vertical offset/baseline term. Not used by Pgopher/Polynom/MultiPolynom.
fit_polynomrank int 2 Polynomial degree used when fit_fitmethod is "Polynom".
fit_polynommaxrank int 10 Highest polynomial degree tried when fit_fitmethod is "MultiPolynom" (the routine tries every rank up to this and keeps the lowest-residual fit).
fit_xpoints int 1000 Number of points used to draw the smooth fitted curve overlay after a fit; only affects the drawn resolution, not the fit itself.
fit_copytoclipboard bool True Whether the fitted line position is automatically copied to the system clipboard right after a successful fit.
fit_comment str "" Default text placed in the "comment" field of every newly-created assignment (from fitting, list assignment, or blend auto-assignment).
Visibility — Toggles for individual UI controls around the main plot.
isvisible_matplotlibtoolbar bool False Shows/hides the standard Matplotlib pan/zoom/save toolbar beneath the main plot.
isvisible_controlsmainplot bool True Shows/hides the in/out/left/right zoom and pan buttons above the main plot.
isvisible_controlsrowscols bool True Shows/hides the rows/columns spinboxes (bound to plot_rows/plot_cols) in the main toolbar.
isvisible_controlswidth bool True Shows/hides the Width control in the main toolbar (and, equivalently, the offset control in the ASAP window).
Colors — Default colors used throughout the main plot, given as hex strings (#rgb, #rrggbb or #rrggbbaa with an alpha channel). All can also be changed interactively per loaded file under Files > Edit Files.
color_exp color #ffffff Default line color for newly-loaded experimental spectrum files.
color_cat color #785ef0 Default color for newly-loaded catalog/prediction files.
color_lin color #648fff Default color for newly-loaded assignment (*.lin) files, and for the quantum-number annotation text when the displayed transition already has a matching assignment.
color_ref color #dc267f Highlight color for the cat stick matching the current reference/series position, for assigned-line markers, and for the offset star markers in ASAP.
color_fit color #fe6100 Color of the fitted curve and its position marker, shown immediately after a fit. Also changeable via Fit > Change Fit Color.
File Formats & General Flags — General behaviour flags, most importantly the custom file-format dictionaries mentioned in Loading Data and accepted Filetypes.
flag_extensions dict {"exp": [".csv"], "cat": [".cat"], "lin": [".lin"], "project": [".files"], "config": [".ini"]} Maps the five recognized file "kinds" — exp, cat, lin, project, config — to a list of file extensions (including the leading dot). Files with an unrecognized extension prompt the user to pick a type interactively.
flag_expformats dict {} Per-extension parser options for experimental spectrum files, e.g. {".txt": {"delimiter": ";", "skiprows": 1}}. The inner dict is passed to pandas' read_csv (via an internal wrapper that otherwise defaults to two unnamed columns, auto-sniffed delimiter, and # as the comment character). Extensions not listed use these auto-detected defaults.
flag_catformats dict {} Per-extension parser options for catalog (*.cat-type) files, to support fixed-width formats other than the native SPCAT layout. The inner dict is passed to pandas' read_fwf, except for the special key "y_is_log" — if truthy, the parsed intensity column is treated as base-10 logarithmic and exponentiated (10**y). Extensions not listed are parsed with the native SPCAT reader.
flag_linformats dict {} Per-extension parser options for assignment (*.lin-type) files, analogous to flag_catformats but without the y_is_log handling (lin files carry no intensity column). Passed to pandas' read_fwf; unlisted extensions use the native SPFIT reader.
flag_saveformat dict {} Custom output format for saving new assignments, structured as {"names": [...columns...], "format": "%.4f" (or a list of formats), "delimiter": " "}, passed to numpy's savetxt. Only used when this dict is non-empty — the default (empty dict) writes the native Pickett *.lin format instead, whose frequency format can be overridden with flag_lincustomfreqformat.
flag_lincustomfreqformat str "" Overrides the frequency-column format used by the native *.lin writer (only relevant when flag_saveformat is empty), e.g. "15.4f". By default Pickett uses a wider format for calculated (unmeasured) lines and a narrower one for measured lines; setting this forces one fixed format for all lines.
flag_tableformatint str ".0f" Python format-spec string used to display integer-valued table cells (Cat/Lin tables).
flag_tableformatfloat str ".2f" Python format-spec string used to display float-valued table cells, and the cursor-position readout in the Close-By-Lines window.
flag_xformatfloat str ".4f" Python format-spec string used for the live cursor x/y position readout on the main plot, and for symmetric tick-label precision.
flag_pyckettquanta int 6 Sets the number of quantum-number columns the underlying pyckett library uses by default when writing native SPFIT/SPCAT-format text (effectively clamped to a minimum of 6 by that library). Independent from series_qns, which controls quantum numbers inside LLWP itself.
flag_notificationtime int 2000 Duration (in milliseconds) a status-bar notification stays visible before disappearing or being replaced by the next queued message.
flag_statusbarmaxcharacters int 100 Maximum character length of a status-bar notification; longer messages are truncated with a trailing ellipsis.
flag_logmaxrows int 1000 Maximum number of rows kept in the Log window; older entries beyond this count are discarded.
flag_appendonsave bool True Whether saving new assignments appends to the chosen file (True) or overwrites it (False). Same as the checkbox beneath the New Assignments table.
flag_showmainplotposition bool True Whether the live cursor x/y position readout is shown while hovering the main plot.
flag_showseriesarrows bool True Whether directional arrows indicating the increment/decrement direction between successive lines of a series are drawn on the plot.
flag_keeponlylastassignment bool False When adding a new assignment, drop any earlier row sharing the same set of quantum numbers, keeping only the most recent assignment per transition.
flag_autoreloadfiles bool True Whether experimental/catalog/assignment files are automatically reloaded when they change on disk.
flag_allowdocking bool True Whether the dockable side windows (Log, New Assignments, Reference Series, …) can be dragged out and undocked/floated.
flag_docksalwaysontop bool True When a dock widget is floated/undocked, whether it stays on top of the main window (True) or behaves as an independent window that can go behind others (False).
flag_confirmdeleteall bool True Whether a confirmation dialog is shown before deleting all rows from New Assignments (the Del All button).
flag_syncreferencestocolumns bool True Whether shrinking plot_cols also removes the corresponding extra Reference Series tabs. Growing the column count always adds tabs regardless of this setting.
Command Line Dialog & Close-By-Lines — The Command Line Dialog (Ctrl+K) is a scripting console distinct from the Cmd Window module below.
commandlinedialog_commands list [] Saved tabs of the Command Line Dialog, a console for running arbitrary Python code snippets inside the running program. Each entry is a 3-item list [title, code, run_on_startup]; entries with run_on_startup = True are executed automatically every time LLWP starts.
commandlinedialog_current int 0 Index of the currently active tab in the Command Line Dialog.
closebylines_catfstring str "{x:12.4f} {qns} {ylog}" Python str.format() template for each catalog-line entry listed in the Close-By-Lines window. Available fields: qns (formatted quantum-number string), ylog (log10 of the intensity), and every column of the catalog file (e.g. x, y, error, elower, tag).
closebylines_linfstring str "{x:12.4f} {qns}" Same templating mechanism as closebylines_catfstring but for assignment (*.lin) entries; no ylog field since lin files carry no intensity.
Residuals — Settings for the Residuals module (Modules > Residuals). Query and variable fields operate on the merged catalog/assignment dataframe, whose columns include qnu1…qnu6, qnl1…qnl6, x_lin, x_cat, error_lin, error_cat, filename_lin, filename_cat, y, degfreed, elower, usd, tag, qnfmt, weight and comment.
residuals_xvariable str "" Expression evaluated to produce the plot's x-axis values. Empty string defaults to x_lin.
residuals_yvariable str "" Expression evaluated to produce the plot's y-axis values. Empty string defaults to x_dev (= x_lin - x_cat). A right-click on the field offers the presets x_lin - x_cat (Obs-calc) and (x_lin - x_cat) / error_lin (Weighted Obs-calc).
residuals_query str "" Filters which matched transitions are plotted; a pandas query expression over the columns listed above. Empty string shows everything.
residuals_colorinput str "" Recolors subsets of points. One rule per line, formatted <hexcolor>; <query> (e.g. #ff0000; qnu1 < 20); later rules override earlier ones and both override residuals_defaultcolor.
residuals_defaultcolor color #000000 Base color for all points before any residuals_colorinput rule is applied.
residuals_blends bool False When enabled, assignments sharing the same observed frequency are treated as one blended line: their predicted frequencies are replaced by the weight-averaged prediction for the group before computing residuals.
residuals_autoscale bool True Whether the plot axes automatically rescale to fit the data on every update.
Blended Lines — Settings for the Blended Lines multi-component fit module (Modules > Blended Lines).
blendedlines_lineshape str "Gauss" Peak-shape model used for the multi-component fit. One of "Gauss", "Lorentz", "Voigt", their "… 1st Derivative"/"… 2nd Derivative" variants, or "FID Fit" (a free-induction-decay/Fourier-transform based multi-peak fit, see blendedlines_fidresolution).
blendedlines_fixedwidth bool False "All Same Width" — when enabled, all peaks in the blend share one common fitted linewidth instead of each having its own.
blendedlines_maxfwhm float 10 Upper bound (in x-axis units) on the FWHM allowed for any fitted peak. 0 falls back to the current plot width.
blendedlines_polynom int 0 Baseline polynomial rank control; the actual number of fitted polynomial terms is this value + 1. -1 disables baseline fitting entirely, 0 fits a constant offset, 1 a linear baseline, and so on.
blendedlines_showbaseline bool True Whether the fitted baseline polynomial curve is drawn (purely a display toggle — does not affect whether a baseline is fit; see blendedlines_polynom).
blendedlines_autopositionpeaks bool True When enabled, the mean of the experimental data in the current view is used as a vertical offset for initial peak-amplitude guesses, so peaks are positioned relative to the local spectrum baseline rather than assumed to start at zero.
blendedlines_fidresolution float 0.05 Frequency resolution requested from the simulated time-domain signal when blendedlines_lineshape is "FID Fit"; smaller values give finer resolution but simulate more time-domain points (slower).
blendedlines_xpoints int 1000 Number of x-sample points used to draw the smooth fitted curve(s) in the (non-FID) Blended Lines plot.
blendedlines_transparency float 0.2 Matplotlib alpha (0–1) used when drawing each individual peak-component curve (not the total fit curve).
blendedlines_color_total color #3d5dff Color of the total/overall fit curve, and (with blendedlines_transparency applied) of each individual peak component.
blendedlines_color_points color #ff3352 Color of the scatter markers placed at each fitted peak's position.
blendedlines_color_baseline color #f6fa14 Color of the drawn baseline polynomial curve.
blendedlines_matplotlibtoolbar bool True Shows/hides the Matplotlib navigation toolbar under the Blended Lines plot.
Create Report — Settings for the Create Report module (Modules > Create Report).
report_query str "" Pandas query expression filtering which assigned transitions are included in the report. Available columns: qnu1…qnu6, qnl1…qnl6, x, error, weight, comment, filename.
report_blends bool True The Blends checkbox — whether assignments sharing the same frequency are treated as a blend in the generated report.
Series Finder — Settings for the Series Finder module (Modules > Series Finder), which searches the loaded catalog for candidate transitions.
seriesfinder_start str "" Lower bound of the searched frequency range. Plain numeric text; empty means no lower bound.
seriesfinder_stop str "" Upper bound of the searched frequency range. Plain numeric text; empty means no upper bound.
seriesfinder_condition str "" Custom pandas query expression ANDed with the range/type filters. Available columns: qnu1…qnu6, qnl1…qnl6, x, error, y, degfreed, elower, usd, tag, qnfmt, filename.
seriesfinder_atype bool True Include a-type transitions (defined in code by the parity of the difference between quantum numbers 2 and 3 of the upper/lower state). All checked type boxes are OR'd together.
seriesfinder_btype bool True Include b-type transitions.
seriesfinder_ctype bool True Include c-type transitions.
seriesfinder_xtype bool True "x-type" — include transitions matching neither a/b/c-type parity. If none of the four type boxes is checked, no type restriction is applied at all.
seriesfinder_onlyunassigned bool True Exclude catalog predictions that already have a matching entry in the loaded *.lin file.
seriesfinder_groupseries bool True Group similar transitions into a single result row (using the active Reference Series tab's quantum-number "diff" pattern to normalize), adding a count column showing how many transitions were grouped. Skipped if no reference-series pattern is set, even when checked.
seriesfinder_results int 10 Maximum number of results shown in the table, taken from the top of the intensity-sorted list.
Peakfinder — Settings for the Peakfinder module (Modules > Peakfinder), which finds peaks in the experimental spectrum via scipy's find_peaks.
peakfinder_kwargs dict {} Parameters passed to scipy's find_peaks, built automatically from the Peakfinder window's Min/Max/Off controls. Recognized keys: "height", "threshold", "distance", "prominence", "width" (each a single minimum value or a [min, max] pair; distance is in samples, not frequency units), plus a special "frequency" key (not passed to scipy) that instead restricts which part of the spectrum is searched.
peakfinder_width float 1 The "Uncertainty unassigned lines" field — maximum distance between a found peak and an already-assigned line for the peak to still count as assigned (and be excluded when peakfinder_onlyunassigned is on). Unrelated to the "width" key inside peakfinder_kwargs, which is scipy's own peak-shape filter.
peakfinder_onlyunassigned bool True Excludes found peaks that fall within peakfinder_width of an already-assigned line.
peakfinder_maxentries int 1000 Caps how many found peaks (sorted by descending intensity) are shown in the results table, for performance. Exporting via Export Peaks is unaffected and always writes every found peak.
peakfinder_peakcolor color #4287f5 Marker color for the found-peaks overlay drawn on the spectrum.
peakfinder_matplotlibtoolbar bool True Shows/hides the Matplotlib navigation toolbar under the Peakfinder plot.
Energy Levels — Settings for the Energy Levels module (Modules > Energy Levels), which plots quantities from a loaded *.egy file. Query and variable fields use the columns qn1…qn6, iblk, indx, egy, err, pmix, we.
energylevels_xvariable str "" Expression evaluated for the x-axis values. Empty defaults to qn1.
energylevels_yvariable str "" Expression evaluated for the y-axis values. Empty defaults to egy.
energylevels_query str "" Pandas query expression filtering which energy levels are plotted; empty shows all.
energylevels_colorinput str "" Per-subset color overrides, one rule per line formatted <hexcolor>;<query>, applied on top of energylevels_defaultcolor.
energylevels_defaultcolor color #000000 Base marker color for all energy-level points before any energylevels_colorinput rule is applied.
energylevels_autoscale bool True Whether the plot axes automatically rescale to fit the data on every update.
On Save — Controls the optional automated pipeline that can run when saving new assignments. The whole pipeline only runs if onsave_consent is True and onsave_skipall is False — both act as safety gates since the pipeline can run external SPFIT/SPCAT programs and rewrite files. Not to be confused with Saving Current Values, which saves the configuration itself.
onsave_skipall bool True Master kill-switch: when enabled, none of the actions below run regardless of the other settings; saving just writes the file.
onsave_clearnewassignments bool True Clears the New Assignments table after saving.
onsave_removeduplicates bool True Deduplicates the *.lin file by quantum numbers, keeping the last occurrence of each transition.
onsave_sort bool True Sorts the *.lin file by the column(s) in onsave_sortkey before writing it.
onsave_sortkey list ["x", "error"] Column name(s), in priority order, used to sort the *.lin file when onsave_sort is enabled — any column of the assignment file, e.g. "x", "error", or a quantum-number column.
onsave_reloadlinfile bool True Reloads the on-disk *.lin file after saving (only needed if flag_autoreloadfiles isn't already handling it).
onsave_increaseparams bool True Updates the SPFIT *.par file's line and parameter counts (NLINE/NPAR) to match the new *.lin file and parameter list.
onsave_runspfit bool True Runs the external SPFIT program on the updated files, and reports fit statistics (WRMS, rejected lines, …).
onsave_runspcat bool True Runs the external SPCAT program after SPFIT, regenerating the *.cat predictions from the newly fitted parameters.
onsave_reloadcatfile bool True Reloads the resulting *.cat file after SPCAT runs.
onsave_updateresiduals bool True Refreshes the Residuals plot (if open) at the end of the pipeline.
Assign All — Settings for the Assign All dialog (Ctrl+Return), which batch-fits and assigns a whole series of predicted lines at once.
assignall_fitwidth float 4 Width of the window around each predicted line position that is actually handed to the fit routine — should be a few linewidths, not the whole plot span.
assignall_plotwidth float 4 Width of the small preview plot shown for each row in the dialog; purely visual context, does not affect the fit.
assignall_maxfwhm float 1 Upper bound on the fitted line's FWHM passed to the fit routine, preventing the unattended batch fitter from converging on a spuriously broad peak.
assignall_maxdegree int 3 Maximum polynomial degree used to predict/interpolate the frequency offset of not-yet-fitted rows from already-fitted ones; automatically reduced when too few points exist.
ASAP — Settings for the Automated Spectral Assignment Procedure — see the ASAP Workflow page for a step-by-step guide. The asap_squared* keys belong to ASAP², a related sub-feature that cross-correlates against the whole loaded catalog rather than a single Reference Series.
asap_stepsize float 6e-6 Grid spacing (in the spectrum's frequency unit) used to build the common x-axis onto which each predicted transition's local experimental intensity is interpolated before being combined into the cross-correlation curve. Should be small relative to the linewidth.
asap_weighted bool True "Weight Transitions" — when enabled, each predicted transition's contribution to the cross-correlation is weighted by its predicted intensity, so strong lines dominate more than weak ones.
asap_minrelratio float 0 Relative-intensity threshold (0–1): predicted lines weaker than this fraction of the strongest prediction in a row are excluded from the cross-correlation. 0 disables the filter.
asap_query str "" Optional expression filtering which predicted transitions of a series are used in the cross-correlation, evaluated against the catalog columns (e.g. quantum numbers, intensity). Empty string uses every predicted transition.
asap_excludearoundassigned float 0 Width of a window blanked out around lines already assigned to a non-reference level, so they don't spuriously influence the cross-correlation of other candidates. 0 disables this.
asap_scaletoexpints bool False "Scale to experimental Intensities" — when enabled, the cross-correlation curve's amplitude is scaled to be physically comparable to experimental/predicted intensities (using asap_expcatfactor) instead of simply normalized to a maximum of 1.
asap_expcatfactor float 1 Empirical scale factor relating experimental to catalog intensities, used only when asap_scaletoexpints is enabled — a calibration constant for the experiment's sensitivity versus the catalog's intensity scale.
asap_catunitconversionfactor float 1/29979.2458 ≈ 3.336e-5 Multiplicative factor applied to every predicted transition frequency read from the *.cat file before use in ASAP. The default converts SPCAT's usual MHz output into cm⁻¹, matching the fixed cm⁻¹ convention of *.egy energy-level files. Set to 1 if your catalog, spectrum and *.egy file already share the same unit.
asap_assigntransitions bool True When a peak is fitted in the ASAP view, whether every predicted transition that contributed to the cross-correlation is individually recorded as a new assignment (True), or only the single reference transition (False).
asap_detailviewerwidth float 0 Width of each sub-plot in the ASAP "Detail Viewer" dock, which shows one mini-plot per predicted transition contributing to a fit. 0 falls back to plot_width.
asap_detailviewerfilter bool True Restricts the Detail Viewer to only the transitions actually used in the cross-correlation (i.e. that passed asap_query/asap_minrelratio), rather than showing every predicted transition of the row.
asap_squaredwidth float 0 In ASAP², the window around each individual catalog transition used for interpolating experimental intensity. 0 falls back to plot_width.
asap_squaredstepsize float 0 Grid step size for the ASAP² correlation x-axis. 0 falls back to asap_stepsize.
asap_squaredfilterquery str "" Pre-filters which catalog lines (from the whole loaded catalog) are included in the ASAP² calculation, e.g. to restrict to a particular band or quantum-number range.
asap_squaredthreshold float 0 Intensity threshold below which interpolated experimental samples are zeroed out before being multiplied into the ASAP² correlation product, reducing noise contribution.
asap_squaredfilterqueryexpdata str "" Advanced per-line Python expression (evaluated with Python's eval, not a pandas query) that can reject a candidate catalog line from the ASAP² product based on its local experimental data window. Empty string disables this check.
asap_squaredplotlog bool False Switches the ASAP² result plot's y-axis to a logarithmic scale.
Cmd Window — Settings for the Cmd Window module (Modules > Cmd Window), which runs shell commands from within LLWP. Distinct from the Command Line Dialog above, which runs Python code rather than shell commands.
cmd_commands list [] Saved tabs of the Cmd Window. Each entry is a 5-item list [title, command, reload_exp, reload_cat, reload_lin] — the tab's title, the shell command text to run (newlines are joined with &&), and three flags controlling which file types are reread after the command finishes.
cmd_current int 0 Index of the currently active tab in the Cmd Window; also the tab used when running a command without specifying one explicitly.