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# print points[0]
labels = []
for i,j in zip(x,y):
label = '<div class="tooltiptext">'
label += '{2}: {1} <br> {3}: {0}'.format(i, j, y_label, x_label)
label += '</div>'
labels.append(label)
tooltip = plugins.PointHTMLTooltip(points[0], labels, hoffset=-tooltipwidth/2, voffset=-tooltipheight, css=css)
plugins.connect(fig, tooltip)
save_name = "{}.html".format(filename.split(".")[0])
# filename = "{}.png".format(filename.split(".")[0])
# plt.savefig(filename, dpi = 300, bbox_inches='tight')
mpld3.save_html(fig, save_name)
plt.close()
# mpld3.fig_to_html(plt_figure)
event_info[1] = int(event_info[1]) - 1
event_info = sp.array(event_info, dtype='str')[sp.newaxis, :]
event_tag = '.%s' % options.event_id
### get all significant events of the current gene
else:
event_info = get_conf_events(options, gid)
plot_event(options, event_info, axes[-1], xlim)
plt.tight_layout()
### save plot into file
if options.format == 'd3':
out_fname = os.path.join(options.outdir, 'plots', 'gene_overview_%s%s%s.html' % (gene.name, event_tag, log_tag))
plugins.clear(fig)
plugins.connect(fig, plugins.Zoom(enabled=True), ClickInfo(sp.ones((10000,), dtype='int')))
mpld3.save_html(fig, open(out_fname, 'w'))
else:
out_fname = os.path.join(options.outdir, 'plots', 'gene_overview_%s%s%s.%s' % (gene.name, event_tag, log_tag, options.format))
plt.savefig(out_fname, format=options.format, bbox_inches='tight')
plt.close(fig)
ind = np.arange(len(innerDict.keys()))
width = 0.35
ax = fig.add_subplot(1,N_CLUSTERS+1,k+2)
rects1 = ax.bar(ind, innerDict.values(), width, color='r')
ax.set_xticklabels(innerDict.keys())
print (innerDict.keys())
blah.append(innerDict)
print (blah)
# plt.show()
with open("output.html", 'w') as f:
mpld3.save_html(fig, f)
mpld3.show()
return
import matplotlib.pyplot as plt, mpld3
fig = plt.figure()
ax = fig.add_subplot(111, axisbg='#EEEEEE')
ax.grid(color='white', linestyle='solid')
for curveName, curve in curves:
if not isinstance(curve[0], pg.basestring):
ax.plot(curve, label=curveName)
ax.legend()
# plt.ylim(0, 100)
plt.title(title)
mpld3.save_html(fig, fileObj)
plt.close(fig)
ylim = max(np.linalg.norm(res[start_idx:], axis=1))
ax.set_ylim([-ylim, ylim])
if int(kind) in SAT_OBS:
svIds = obs[kind]['svIds']
for svId in set(svIds):
svId_idx = (svIds == svId)
t = obs[kind]['t'][svId_idx]
res = obs[kind]['residual'][svId_idx]
ax.plot(t, res, label='SV ' + str(int(svId)))
ax.legend(loc='right')
else:
ax.plot(t, res)
plt.title('Residual of kind ' + ObservationKind.to_string(int(kind)), fontsize=20)
plt.tight_layout()
os.makedirs(save_path)
mpld3.save_html(fig, save_path + 'residuals_plot.html')
output = a[i]**-0.5 * amp * (t-b[j])/a[i] * exp(-( (t-b[j])/a[i] )**2.0)
return output
W[i][j]=quad(integrand1, 1, 3)[0]
fig, ax = plt.subplots()
im = ax.pcolormesh(a,b,W)
#plt.show()
fig.colorbar(im, ax=ax)
ax.set_title('An Image', size=20)
mpld3.fig_to_html(fig)
mpld3.show()
mpld3.save_html(fig, "Wavelet.html")
def render_mpl(self, fig, path, **kwargs):
import mpld3
kwargs.pop('dpi')
mpld3.save_html(
fig,
fileobj=path,
**kwargs)
sorted_keys=sorted(xl_list[0].keys())
for k in sorted_keys:
df[k] = np.array([xl[k] for xl in xl_list])
labels = []
for i in range(len(xl_labels)):
label = df.ix[[i], :].T
# .to_html() is unicode; so make leading 'u' go away with str()
labels.append(str(label.to_html()))
tooltip = plugins.PointHTMLTooltip(points, labels,
voffset=10, hoffset=10, css=css)
plugins.connect(fig, tooltip)
mpld3.save_html(fig,"output.html")