def test_mixed_digestions(tmpdir):
png_path = os.path.join(str(tmpdir), "test.png")
enzymes = "EcoRI", "EcoRV", "BamHI", "XhoI"
mixes = [[e] for e in enzymes] + list(itertools.combinations(enzymes, 2))
patterns = [
BandsPattern(
compute_digestion_bands(example_sequence, mix, linear=True),
ladder=LADDER_100_to_4k,
label=" + ".join(mix),
label_fontdict={
"rotation": 40,
"size": 9
},
) for mix in mixes
]
patterns_set = BandsPatternsSet(
patterns=[LADDER_100_to_4k] + patterns,
ladder=LADDER_100_to_4k,
label="Digestion results",
ladder_ticks=3,
)
ax = patterns_set.plot()
ax.figure.savefig(png_path, bbox_inches="tight", dpi=200)
assert os.path.exists(png_path)
def draw_gel(self, digest_metadata, xlabel, output_dir):
strain_name = digest_metadata['ID']
cpn60UT_ladder = custom_ladder(
"cpn60UT", {
25: 250,
50: 225,
100: 205,
200: 186,
300: 171,
400: 158,
500: 149,
600: 139
})
LADDER_100_to_1k = custom_ladder(
"cpn60UT", {
25: 249,
50: 226,
100: 205,
200: 186,
300: 171,
400: 158,
500: 149,
650: 139,
850: 128,
1000: 121
})
# ladder = cpn60UT_ladder.modified(background_color="#E2EDFF", label_fontdict={"rotation": -90}, label="MW")
ladder = LADDER_100_to_1k.modified(background_color="#E2EDFF",
label_fontdict={"rotation": -90},
label="MW")
patterns = []
for renzyme in sorted(self.renzymes):
patterns.append(
BandsPattern(digest_metadata[str((renzyme, 'Band Sizes'))],
ladder,
label_fontdict={"rotation": -90},
label=renzyme))
# patterns_set = BandsPatternsSet(patterns=[ladder] + patterns, ladder=ladder, label_fontdict={"size": 7}, label="Migration Distance", ladder_ticks=3)
patterns_set = BandsPatternsSet(patterns=[ladder] + patterns,
ladder=ladder,
ladder_ticks=3)
ax = patterns_set.plot()
ax.set_xlabel(xlabel)
strain_filename = strain_name.replace("/", "-").replace("(",
"_").replace(
")", "_")
outfile = os.path.join(output_dir, strain_filename + ".png")
if not os.path.exists(outfile):
ax.figure.savefig(outfile, bbox_inches="tight", dpi=600)
return outfile
def test_simple_band_pattern(tmpdir):
png_path = os.path.join(str(tmpdir), "test.png")
patterns = [
BandsPattern([100, 500, 3500], ladder, label="C1"),
BandsPattern([300, 400, 1500], ladder, label="C2"),
BandsPattern([100, 1200, 1400, 3000], ladder, label="C3"),
BandsPattern([100, 700], ladder, label="C4"),
BandsPattern([200], ladder, label="C4", band_is_uncut=True),
]
patterns_set = BandsPatternsSet(patterns=[ladder] + patterns,
ladder=ladder,
label="Digests",
ladder_ticks=3)
ax = patterns_set.plot()
ax.figure.savefig(png_path, bbox_inches="tight", dpi=200)
assert os.path.exists(png_path)
def test_simple_digestions_matplotlib_plot(tmpdir):
png_path = os.path.join(str(tmpdir), "test.png")
patterns = [
BandsPattern(
compute_digestion_bands(example_sequence, [enzyme]),
ladder=LADDER_100_to_4k,
label=enzyme,
global_bands_props={"label": "=size"},
) for enzyme in ["BamHI", "EcoRI", "EcoRV", "PstI", "SpeI", "XbaI"]
]
patterns_set = BandsPatternsSet(
patterns=[LADDER_100_to_4k] + patterns,
ladder=LADDER_100_to_4k,
label="Digestion results",
ladder_ticks=3,
)
ax = patterns_set.plot()
ax.figure.savefig(png_path, bbox_inches="tight", dpi=200)
assert os.path.exists(png_path)
def test_customized_band_pattern(tmpdir):
band_image_path = os.path.join("tests", "data", "band_image.png")
png_path = os.path.join(str(tmpdir), "test.png")
gel_image = mpimg.imread(band_image_path)
patterns = [
BandsPattern(
[100, 1500, 2000, 1000, 3500],
ladder,
label="C1",
corner_note="corner note",
corner_note_fontdict=None,
background_color="#eeeeff",
gel_image=gel_image,
)
]
patterns_set = BandsPatternsSet(patterns=[ladder] + patterns,
ladder=ladder,
label="Digests",
ladder_ticks=3)
ax = patterns_set.plot()
ax.figure.savefig(png_path, bbox_inches="tight", dpi=200)
assert os.path.exists(png_path)
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon May 27 09:46:13 2019
@author: bjorn
"""
from bandwagon import BandsPattern, BandsPatternsSet, LADDER_100_to_4k
ladder = LADDER_100_to_4k.modified(label="Ladder", background_color="#ffffaf")
patterns = [
BandsPattern([100, 500, 3500], ladder, label="C1"),
BandsPattern([300, 400, 1500], ladder, label="C2"),
BandsPattern([100, 1200, 1400, 3000], ladder, label="C3"),
BandsPattern([100, 700], ladder, label="C4"),
]
patterns_set = BandsPatternsSet(patterns=[ladder] + patterns,
ladder=ladder,
label="Test pattern",
ladder_ticks=3)
ax = patterns_set.plot()
#ax.figure.savefig("simple_band_patterns.png", bbox_inches="tight", dpi=200)
def write_identification_report(
self,
target_file=None,
relative_tolerance=0.05,
min_band_cutoff=None,
max_band_cutoff=None,
):
"""Plot a Graphic report of the gel validation.
The report displays the patterns, with green and red backgrounds
depending on whether they passed the validation test.
Parameters
----------
target_file
File object or file path where to save the figure. If provided, the
function returns none, else the function returns the axes array of
the final figure
relative_tolerance
Relative error tolerated on each band for the ovserved patterns to
be considered similar to the expected patterns.
min_band_cutoff
Bands with a size below this value will not be considered
max_band_cutoff
Bands with a size above this value will not be considered
"""
bands_validities = self.compute_all_bands_validities(
relative_tolerance=relative_tolerance,
min_band_cutoff=min_band_cutoff,
max_band_cutoff=max_band_cutoff,
)
L = len(self.constructs_records)
max_x = (
max(len(measures)
for measures in self.observed_bands.values()) + 1)
fig, axes = plt.subplots(L, 1, figsize=(2.2 * max_x, 3 * L))
axes_validities = zip(axes, bands_validities.items())
for ax, (construct_id, validities) in axes_validities:
reference = BandsPattern(
self.expected_bands[construct_id],
ladder=self.ladder,
label="exp.",
background_color="#c6dcff",
corner_note="Total: %d bp" %
sum(self.expected_bands[construct_id]),
global_bands_props={"label_fontdict": {
"size": 5
}},
)
sorted_bands = sorted(reference.bands, key=lambda b: -b.dna_size)
for band_name, band in zip("abcdefghijklm", sorted_bands):
band.label = band_name
patterns = [
BandsPattern(
self.observed_bands[construct_id][measure_name],
corner_note="Total: %d bp" %
sum(self.observed_bands[construct_id][measure_name]),
ladder=self.ladder,
label=measure_name,
gel_image=self.migration_images[measure_name],
background_color="#aaffaa"
if validities[measure_name] else "#ffaaaa",
) for measure_name in self.observed_bands[construct_id]
]
patterns_set = BandsPatternsSet(
[reference] + patterns,
ladder=self.ladder,
label=construct_id,
ladder_ticks=5,
global_patterns_props={"label_fontdict": {
"rotation": 60
}},
)
ax.set_xlim(0.5, max_x + 2)
patterns_set.plot(ax)
fig.subplots_adjust(hspace=0.3)
if target_file is not None:
fig.savefig(target_file, bbox_inches="tight")
plt.close(fig)
else:
return axes