Making Single Strand DNA Models

It is recommended that you run this example inside a Jupyter environment rather than a VSCode or similar environment

This requires the mayavi jupyter extension jupyter nbextension install --py mayavi --user

import sys
from pathlib import Path

try:
    from fractaldna.dna_models import dnachain as dna
except (ImportError, ModuleNotFoundError):
    # Path modifications if working straight out of the git repo.
    sys.path.append(str(Path.cwd().parent.parent.parent))
    from fractaldna.dna_models import dnachain as dna

from mayavi import mlab

# Disable this option for interactive rendering
mlab.options.offscreen = True

# Enable this option for an interactive notebook
# mlab.init_notebook()

Making and plotting a single DNA strand

# Make a 40 base pair long DNA Strand
chain = dna.DNAChain("GTAC" * 10)
# Generate a simple Matplotlib visualisation
# The basic plot shows each molecule as a point
plot = chain.to_plot()
plot.gca().set_title("Basic Plot")

# You can also hide certain molecules (b = base, s=sugar, p=phosphate)
plot_phosphate = chain.to_plot(plot_b=False, plot_s=False, plot_p=True)
plot_phosphate.gca().set_title("Phosptate Only Plot")

# The surface plot plots each DNA molecule as a ball
plot_surface = chain.to_surface_plot()
plot_surface.gca().set_title("Surface Plot")

Text(0.5, 0.92, 'Surface Plot')

Generating pretty plots with MayaVI

# MayaVI can generate nicer plots, joining the strands together
plot = chain.to_strand_plot()
plot.scene.save_jpg("single_strand_strand_plot.jpg")

# Or you can just plot the path of the entire block of dna, which looks better for a curved chain
chain = dna.TurnedDNAChain("GATC" * 40)
plot = chain.to_line_plot()
plot.scene.save_jpg("single_turned_strand_line_plot.jpg")

plot = chain.to_strand_plot()
plot.scene.save_jpg("single_turned_strand_strand_plot.jpg")

Exporting a DNA strand as text

# The chain can be converted to a text stream for saving
print(chain.to_text()[:1000], "...")

#NAME SHAPE CHAIN_ID STRAND_ID BP_INDEX SIZE_X SIZE_Y SIZE_Z POS_X POS_Y POS_Z ROT_X ROT_Y ROT_Z
Phosphate sphere 0 0 0 2.2823538668497223 2.2823538668497223 2.2823538668497223 -0.779890171626023 8.815584979134911 -333.92471210406507 0.0 -0.0 0.0
Sugar sphere 0 0 0 2.632139825596463 2.632139825596463 2.632139825596463 2.2598223909714656 6.737434473918255 -334.824704023257 0.0 -0.0 0.0
Guanine ellipse 0 0 0 3.6315030254147858 3.799953276546786 1.8872880374815397 0.6081393104497743 2.3215301459187865 -335.84706382820303 0.0 -0.0 0.0
Phosphate sphere 0 1 0 2.2823538668497223 2.2823538668497223 2.2823538668497223 -0.779890171626023 -8.815584979134911 -338.19297877073177 0.0 -0.0 0.0
Sugar sphere 0 1 0 2.632139825596463 2.632139825596463 2.632139825596463 2.2598223909714656 -6.737434473918255 -337.2929868515398 0.0 -0.0 0.0
Cytosine ellipse 0 1 0 3.597341307934331 3.066331331321459 1.7793608554794114 0.035998166959542686 -3.3433274569807168 -336.3976643350362 0.0 -0.0 0.0
Phosphate sphere 0 ...

# Or a DataFrame
chain.to_frame()

	name	shape	chain_idx	strand_idx	bp_idx	size_x	size_y	size_z	pos_x	pos_y	pos_z	rot_x	rot_y	rot_z
0	Phosphate	sphere	0	0	0	2.282354	2.282354	2.282354	-0.779890	8.815585	-333.924712	0.000000	-0.000000	0.000000
1	Sugar	sphere	0	0	0	2.632140	2.632140	2.632140	2.259822	6.737434	-334.824704	0.000000	-0.000000	0.000000
2	Guanine	ellipse	0	0	0	3.631503	3.799953	1.887288	0.608139	2.321530	-335.847064	0.000000	-0.000000	0.000000
3	Phosphate	sphere	0	1	0	2.282354	2.282354	2.282354	-0.779890	-8.815585	-338.192979	0.000000	-0.000000	0.000000
4	Sugar	sphere	0	1	0	2.632140	2.632140	2.632140	2.259822	-6.737434	-337.292987	0.000000	-0.000000	0.000000
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
1	Sugar	sphere	0	0	159	2.632140	2.632140	2.632140	337.292987	5.809905	4.092044	1.570796	0.633555	1.570796
2	Cytosine	ellipse	0	0	159	3.597341	3.066331	1.779361	336.397664	2.008306	2.673171	1.570796	0.633555	1.570796
3	Phosphate	sphere	0	1	159	2.282354	2.282354	2.282354	333.924712	-5.847478	-6.643024	1.570796	0.633555	1.570796
4	Sugar	sphere	0	1	159	2.632140	2.632140	2.632140	334.824704	-2.167395	-6.767734	1.570796	0.633555	1.570796
5	Guanine	ellipse	0	1	159	3.631503	3.799953	1.887288	335.847064	-0.884260	-2.231013	1.570796	0.633555	1.570796

960 rows × 14 columns