import numpy as np
import logging
from nanoplotter.plot import Plot
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
class Layout(object):
def __init__(self, structure, template, xticks, yticks, flowcell):
self.structure = structure
self.template = template
self.xticks = xticks
self.yticks = yticks
self.flowcell = flowcell
def make_layout(maxval):
"""Make the physical layout of the MinION flowcell.
based on https://bioinformatics.stackexchange.com/a/749/681
returned as a numpy array
"""
if maxval < 127: # Flongle up to channel 126
return Layout(
structure=np.array([
list(range(1, 13)) + [0],
list(range(13, 25)) + [0],
range(25, 38),
range(38, 51),
range(51, 64),
range(64, 77),
range(77, 90),
range(90, 103),
list(range(103, 115)) + [0],
list(range(115, 127)) + [0]
]),
template=np.zeros((10, 13)),
xticks=range(1, 14),
yticks=range(1, 11),
flowcell='Flongle')
elif maxval < 513: # MinION up to channel 512
layoutlist = []
for i, j in zip(
[33, 481, 417, 353, 289, 225, 161, 97],
[8, 456, 392, 328, 264, 200, 136, 72]):
for n in range(4):
layoutlist.append(list(range(i + n * 8, (i + n * 8) + 8, 1))
+ list(range(j + n * 8, (j + n * 8) - 8, -1)))
return Layout(
structure=np.array(layoutlist).transpose(),
template=np.zeros((16, 32)),
xticks=range(1, 33),
yticks=range(1, 17),
flowcell='MinION')
else: # Assuming PromethION
return Layout(
structure=np.concatenate([np.array([list(range(10 * i + 1, i * 10 + 11))
for i in range(25)]) + j
for j in range(0, 3000, 250)],
axis=1),
template=np.zeros((25, 120)),
xticks=range(1, 121),
yticks=range(1, 26),
flowcell='PromethION')
def spatial_heatmap(array, path, title=None, color="Greens", figformat="png"):
"""Taking channel information and creating post run channel activity plots."""
logging.info("Nanoplotter: Creating heatmap of reads per channel using {} reads."
.format(array.size))
activity_map = Plot(
path=path + "." + figformat,
title="Number of reads generated per channel")
layout = make_layout(maxval=np.amax(array))
valueCounts = pd.value_counts(pd.Series(array))
for entry in valueCounts.keys():
layout.template[np.where(layout.structure == entry)] = valueCounts[entry]
plt.figure()
ax = sns.heatmap(
data=pd.DataFrame(layout.template, index=layout.yticks, columns=layout.xticks),
xticklabels="auto",
yticklabels="auto",
square=True,
cbar_kws={"orientation": "horizontal"},
cmap=color,
linewidths=0.20)
ax.set_title(title or activity_map.title)
activity_map.fig = ax.get_figure()
activity_map.save(format=figformat)
plt.close("all")
return [activity_map]
