Visualization

spxtacular uses Plotly for interactive HTML visualizations. All three functions return a plotly.graph_objects.Figure object. Plotly is an optional dependency — install it with pip install plotly.

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plot_spectrum()

from spxtacular.visualization import plot_spectrum

fig = plot_spectrum(
    spectrum,
    title=None,          # plot title
    show_charges=True,   # colour sticks by charge state
    show_scores=True,    # annotate scored peaks with their score value
    **layout_kwargs,     # passed to fig.update_layout()
)
fig.show()

Draws a stick plot of any Spectrum. When charge is present, sticks are coloured by charge state (z=1, z=2, ... in different colours; z=-1 singletons in grey). When score is present and show_scores=True, score values are shown above each scored peak.

Spectrum.plot() is a convenience wrapper around this function:

spec.plot(title="My spectrum", show_charges=True).show()

Raw spectrum:

Deconvoluted spectrum (coloured by charge state):

Deconvoluted + filtered (score ≥ 0.5):

---

mirror_plot()

from spxtacular.visualization import mirror_plot

fig = mirror_plot(
    raw,             # Spectrum -- drawn inverted below the x-axis
    decon,           # Spectrum -- drawn upright above the x-axis
    title=None,
    normalize=True,  # scale each half to its own maximum independently
    show_scores=True,
    **layout_kwargs,
)
fig.show()

Mirror plot for comparing a raw spectrum (inverted, below) against its deconvoluted counterpart (upright, above). Useful for visually confirming that isotope clusters have been correctly identified and scored. Deconvoluted peaks are coloured by charge state; score annotations appear above each cluster.

Example:

from spxtacular import Spectrum
from spxtacular.visualization import mirror_plot

decon = spec.deconvolute(charge_range=(1, 5), tolerance=10, tolerance_type="ppm")
fig = mirror_plot(spec, decon, title="Raw vs deconvoluted")
fig.show()

Raw vs deconvoluted:

Raw vs deconvoluted + filtered:

Neutral mass spectrum:

Neutral mass + filtered:

---

annotate_spectrum()

import peptacular as pt
from spxtacular.visualization import annotate_spectrum

fragments = pt.fragment("PEPTIDE", ion_types=("b", "y"), charges=(1, 2))
fig = annotate_spectrum(
    spectrum,
    fragments,
    mz_tol=0.02,
    mz_tol_type="da",   # or "ppm"
    title=None,
    **layout_kwargs,
)
fig.show()

Draws the spectrum as a stick plot and overlays matched fragment ion labels (b/y ions coloured by ion type). Unmatched peaks are shown in grey.

Parameters:

Parameter	Default	Description
spectrum		Spectrum to plot
fragments		Iterable of fragment objects from peptacular
mz_tol	0.02	Matching tolerance
mz_tol_type	"da"	"da" or "ppm"
title	None	Plot title

Annotated spectrum: