tis = ht.argmax(axis=0)
colors = cm.jet(1.0 * ht.argmax(axis=0) / len(indt))
# 2D plot
fig, axs = plt.subplots(1, 2, figsize=(12, 6))
ax = axs[0]
ax.scatter(M3[0], M3[1], color=colors)
ax.set_xlabel('PC1')
ax.set_ylabel('PC2')
ax.set_title(', '.join([patient.code] + map(str, roi)))
ax.grid(True)
# Haplotype trajectories
from hivwholeseq.patients.get_local_haplotypes import plot_haplotype_frequencies
plot_haplotype_frequencies(patient.times[indt], hft,
figax=(fig, axs[1]),
title=patient.name+', '+' '.join(map(str, roi)))
#axs[1].set_yscale('logit')
# 3D plot
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter(M3[0], M3[1], M3[2], color=colors)
ax.set_xlabel('PC1')
ax.set_ylabel('PC2')
ax.set_zlabel('PC3')
ax.set_title(', '.join([patient.code] + map(str, roi)))
if use_plot:
plt.ion()
if use_plot:
import matplotlib.pyplot as plt
from hivwholeseq.patients.get_local_haplotypes import plot_haplotype_frequencies
def on_click(event):
'''Print sequence on click'''
mouseevent = event.mouseevent
artist = event.artist
i_clicked = int(artist.get_label())
(score, ali1, ali2) = align_global(seq0, seqs[i_clicked], score_gapopen=-20)
pretty_print_pairwise_ali((ali1, ali2), name1='cons0', name2='clicked', width=120)
(fig, ax) = plot_haplotype_frequencies(patient.times[ind], hft,
title=patient.name+', '+stname,
picker=0.1)
fig.canvas.mpl_connect('pick_event', on_click)
plt.ion()
plt.show()
# Predict RNA structures
structs = []
for i, seq in enumerate(seqs):
if VERBOSE >= 2:
print 'Predicting structure n', i+1, 'of', len(seqs)
label = stname+'_'+str(i)
colors = cm.jet(1.0 * ht.argmax(axis=0) / len(indt))
# 2D plot
fig, axs = plt.subplots(1, 2, figsize=(12, 6))
ax = axs[0]
ax.scatter(M3[0], M3[1], color=colors)
ax.set_xlabel('PC1')
ax.set_ylabel('PC2')
ax.set_title(', '.join([patient.code] + map(str, roi)))
ax.grid(True)
# Haplotype trajectories
from hivwholeseq.patients.get_local_haplotypes import plot_haplotype_frequencies
plot_haplotype_frequencies(patient.times[indt],
hft,
figax=(fig, axs[1]),
title=patient.name + ', ' +
' '.join(map(str, roi)))
#axs[1].set_yscale('logit')
# 3D plot
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter(M3[0], M3[1], M3[2], color=colors)
ax.set_xlabel('PC1')
ax.set_ylabel('PC2')
ax.set_zlabel('PC3')
ax.set_title(', '.join([patient.code] + map(str, roi)))
if use_plot:
plt.ion()
