from dna_features_viewer import GraphicFeature, GraphicRecord
features=[
    GraphicFeature(start=0, end=20, strand=+1, color="#ffd700",
                   label="Small feature"),
    GraphicFeature(start=20, end=500, strand=+1, color="#ffcccc",
                   label="Gene 1 with a very long name"),
    GraphicFeature(start=400, end=700, strand=-1, color="#cffccc",
                   label="Gene 2"),
    GraphicFeature(start=600, end=900, strand=+1, color="#ccccff",
                   label="Gene 3")
]
record = GraphicRecord(sequence_length=1000, features=features)
record.plot(figure_width=5)

from dna_features_viewer import GraphicFeature, GraphicRecord

sequence = "ATGCATGCATGCATGCATGCATGCATGC"
record = GraphicRecord(sequence=sequence, features=[
    GraphicFeature(start=5, end=10, strand=+1, color='#ffcccc'),
    GraphicFeature(start=8, end=15, strand=+1, color='#ccccff')
])

ax, _ = record.plot(figure_width=5)
record.plot_sequence(ax)
record.plot_translation(ax, (8, 23), fontdict={'weight': 'bold'})
ax.figure.savefig('sequence_and_translation.png', bbox_inches='tight')

...
record.plot(ax=ax1)
cropped_record = record.crop((zoom_start, zoom_end))
cropped_record.plot(ax=ax2)
cropped_record.plot_sequence(ax=ax2)
cropped_record.plot_translation(ax=ax2, location=(408, 423))

from dna_features_viewer import BiopythonTranslator
graphic_record = BiopythonTranslator().translate_record("my_sequence.gb")
ax, _ = graphic_record.plot(figure_width=10, strand_in_label_threshold=7)

import matplotlib.pyplot as plt
from dna_features_viewer import BiopythonTranslator
from Bio import SeqIO
import numpy as np

fig, (ax1, ax2) = plt.subplots(
    2, 1, figsize=(12, 3), sharex=True, gridspec_kw={"height_ratios": [4, 1]}
)

# PLOT THE RECORD MAP
record = SeqIO.read("example_sequence.gb", "genbank")
graphic_record = BiopythonTranslator().translate_record(record)
graphic_record.plot(ax=ax1, with_ruler=False, strand_in_label_threshold=4)

# PLOT THE LOCAL GC CONTENT (we use 50bp windows)
gc = lambda s: 100.0 * len([c for c in s if c in "GC"]) / 50
xx = np.arange(len(record.seq) - 50)
yy = [gc(record.seq[x : x + 50]) for x in xx]
ax2.fill_between(xx + 25, yy, alpha=0.3)
ax2.set_ylim(bottom=0)
ax2.set_ylabel("GC(%)")

graphic_record.plot_on_multiple_pages(
    "multipage_plot.pdf",
    nucl_per_line=70,
    lines_per_page=7,
    plot_sequence=True
)

from dna_features_viewer import BiopythonTranslator

class MyCustomTranslator(BiopythonTranslator):
    """Custom translator implementing the following theme:

    - Color terminators in green, CDS in blue, all other features in gold.
    - Do not display features that are restriction sites unless they are BamHI
    - Do not display labels for restriction sites
    - For CDS labels just write "CDS here" instead of the name of the gene.

    """

    def compute_feature_color(self, feature):
        if feature.type == "CDS":
            return "blue"
        elif feature.type == "terminator":
            return "green"
        else:
            return "gold"

    def compute_feature_label(self, feature):
        if feature.type == 'restriction_site':
            return None
        elif feature.type == "CDS":
            return "CDS here"
        else:
            return BiopythonTranslator.compute_feature_label(self, feature)

    def compute_filtered_features(self, features):
        """Do not display promoters. Just because."""
        return [
            feature for feature in features
            if (feature.type != "restriction_site")
            or ("BamHI" in str(feature.qualifiers.get("label", '')))
        ]


graphic_record = MyCustomTranslator().translate_record("example_sequence.gb")
ax, _ = graphic_record.plot(figure_width=10)
ax.figure.tight_layout()
ax.figure.savefig("custom_bopython_translator.png")