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()