prolint.plotting.residues

Residue metrics plotters for per-residue visualization.

This module provides bar charts and logo grids for displaying per-residue contact metrics.

Classes

ResidueMetricsPlotter	Plotter for per-residue contact metrics.
LogoGridPlotter	Plotter for grid-based residue logo visualization.

Module Contents

class prolint.plotting.residues.ResidueMetricsPlotter

Bases: prolint.plotting.base.BasePlotter

Plotter for per-residue contact metrics.

Visualizes metrics as bar charts or scatter plots with amino acid coloring and highlighting options.

See also

MetricsAnalysis

Generates per-residue metric data

LogoGridPlotter

Grid-based residue visualization

name = 'residue_metrics'

required_analysis = 'metrics'

description = 'Per-residue metrics visualization (bar/scatter)'

classmethod validate_result(result: prolint.analysis.base.AnalysisResult) → None

Validate that result contains residue metrics data.

classmethod plot(result: prolint.analysis.base.AnalysisResult, style: str = 'bar', colorscheme: str = 'prolint', xlabel: str = 'Residue', ylabel: str = 'Value', title: str = 'Per-Residue Metrics', figsize: Tuple[float, float] | None = None, ax: matplotlib.axes.Axes | None = None, show_aa_labels: bool = True, highlight_residues: List[int] | None = None, bar_width: float = 0.8, sort_by_value: bool = False, marker_size: int = 50) → Tuple[matplotlib.figure.Figure, matplotlib.axes.Axes]

Create per-residue metrics visualization.

Parameters:

• result (AnalysisResult) – Result from metrics analysis.

• style ({"bar", "scatter"}, default="bar") – Plot style.

• colorscheme (str, default="prolint") – Color scheme (“prolint”, “amino_acid”, or scale name).

• show_aa_labels (bool, default=True) – Whether to show amino acid labels on x-axis.

• highlight_residues (list of int, optional) – Residue IDs to highlight.

• sort_by_value (bool, default=False) – Whether to sort residues by value.

• ax (Axes, optional) – Existing axes to plot on.

Returns:

Matplotlib figure and axes objects.

Return type:

tuple of (Figure, Axes)

class prolint.plotting.residues.LogoGridPlotter

Bases: prolint.plotting.base.BasePlotter

Plotter for grid-based residue logo visualization.

Displays residues as colored cells arranged in rows with one-letter amino acid codes and residue numbers.

See also

MetricsAnalysis

Generates per-residue metric data

ResidueMetricsPlotter

Bar/scatter visualization

name = 'logo_grid'

required_analysis = 'metrics'

description = 'Grid-based residue logo plot with amino acid annotations'

classmethod validate_result(result: prolint.analysis.base.AnalysisResult) → None

Validate that result contains residue metrics data.

classmethod plot(result: prolint.analysis.base.AnalysisResult, colorscheme: str = 'prolint', residues_per_row: int = 80, cell_size: float = 0.3, title: str = 'Residue Logo Plot', figsize: Tuple[float, float] | None = None, highlight_residues: List[int] | None = None) → Tuple[matplotlib.figure.Figure, matplotlib.axes.Axes]

Create grid-based residue logo visualization.

Parameters:

• result (AnalysisResult) – Result from metrics analysis.

• colorscheme (str, default="prolint") – Color scale name for value-based coloring.

• residues_per_row (int, default=80) – Number of residue cells per row.

• cell_size (float, default=0.3) – Size of each cell in inches.

• title (str, default="Residue Logo Plot") – Plot title.

• figsize (tuple of (float, float), optional) – Figure dimensions (width, height). Auto-calculated if None.

• highlight_residues (list of int, optional) – Residue IDs to highlight with colored borders.

Returns:

Matplotlib figure and axes objects.

Return type:

tuple of (Figure, Axes)