Example script that demonstrates how to combine different multi-row plots

combined_plots.py

# Code source: Patrick Kunzmann
# License: BSD 3 clause

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import biotite
import biotite.sequence as seq
import biotite.sequence.graphics as graphics
import biotite.sequence.io.genbank as gb
import biotite.sequence.align as align
import biotite.database.entrez as entrez


LENGTH_PER_ROW = 100


# Create 'FeaturePlotter' subclasses
# for drawing the scondary structure features

class HelixPlotter(graphics.FeaturePlotter):

    def __init__(self):
        pass

    # Check whether this class is applicable for drawing a feature
    def matches(self, feature):
        if feature.key == "SecStr":
            if "sec_str_type" in feature.qual:
                if feature.qual["sec_str_type"] == "helix":
                    return True
        return False
    
    # The drawing function itself
    def draw(self, axes, feature, bbox, loc, style_param):
        # Approx. 1 turn per 3.6 residues to resemble natural helix
        n_turns = np.ceil((loc.last - loc.first + 1) / 3.6)
        x_val = np.linspace(0, n_turns * 2*np.pi, 100)
        # Curve ranges from 0.3 to 0.7
        y_val = (-0.4*np.sin(x_val) + 1) / 2
        
        # Transform values for correct location in feature map
        x_val *= bbox.width / (n_turns * 2*np.pi)
        x_val += bbox.x0
        y_val *= bbox.height
        y_val += bbox.y0
        
        # Draw white background to overlay the guiding line
        background = Rectangle(
            bbox.p0, bbox.width, bbox.height, color="white", linewidth=0
        )
        axes.add_patch(background)
        axes.plot(
            x_val, y_val, linewidth=2, color=biotite.colors["dimgreen"]
        )


class SheetPlotter(graphics.FeaturePlotter):

    def __init__(self, head_width=0.8, tail_width=0.5):
        self._head_width = head_width
        self._tail_width = tail_width


    def matches(self, feature):
        if feature.key == "SecStr":
            if "sec_str_type" in feature.qual:
                if feature.qual["sec_str_type"] == "sheet":
                    return True
        return False
    
    def draw(self, axes, feature, bbox, loc, style_param):
        x = bbox.x0
        y = bbox.y0 + bbox.height/2
        dx = bbox.width
        dy = 0
        
        if  loc.defect & seq.Location.Defect.MISS_RIGHT:
            # If the feature extends into the prevoius or next line
            # do not draw an arrow head
            draw_head = False
        else:
            draw_head = True
        
        axes.add_patch(biotite.AdaptiveFancyArrow(
            x, y, dx, dy,
            self._tail_width*bbox.height, self._head_width*bbox.height,
            # Create head with 90 degrees tip
            # -> head width/length ratio = 1/2
            head_ratio=0.5, draw_head=draw_head,
            color=biotite.colors["orange"], linewidth=0
        ))


# Fetch GenBank files of the TK's first chain and extract annotatation
gb_file = gb.GenBankFile.read(
    entrez.fetch("1QGD_A", None, "gb", "protein", "gb")
)
annotation = gb.get_annotation(gb_file, include_only=["SecStr"])
sequence = gb.get_sequence(gb_file, "gp")
# Length of the sequence
_, length, _, _, _, _ = gb.get_locus(gb_file)


# Toy alignment of the sequence with itself
matrix = align.SubstitutionMatrix.std_protein_matrix()
alignment = align.align_ungapped(sequence, sequence, matrix)


fig, axes = plt.subplots(
    nrows=2 * int(np.ceil(length/LENGTH_PER_ROW)),
    figsize=(8.0, 12.0)
)

for i, start in enumerate(np.arange(0, length+1, LENGTH_PER_ROW)):
    graphics.plot_feature_map(
        axes[2*i], annotation,
        symbols_per_line=LENGTH_PER_ROW, show_numbers=True,
        # 'loc_range' takes exclusive stop -> length+1 is required
        loc_range=(start+1, start+LENGTH_PER_ROW+1),
        feature_plotters=[HelixPlotter(), SheetPlotter()]
    )

    graphics.plot_alignment_similarity_based(
        axes[2*i+1], alignment[start:start+LENGTH_PER_ROW], matrix=matrix,
        symbols_per_line=LENGTH_PER_ROW, show_numbers=True,
    )

fig.tight_layout()

plt.savefig("combined_plots.png")