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# print(x[min_index])
# Xlim = maxXlim - minXlim
# ax.axhline(y=1, xmin=(x[peak_index]-minXlim)/Xlim, ls='--', color='r')
# ax.axhline(y=0, xmin=(x[min_index]-minXlim)/Xlim, ls='--', color='r')
# 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)
)
f.tight_layout() #Padding around plot
lines = ax.get_lines()
plt.close(f)
#http://mpld3.github.io/modules/API.html
if self.interactive:
import mpld3
if self.selectlines:
from line_plugin import HighlightLines
for idx, col in enumerate(self.spec_modified.columns):
name = 'COLUMN(%s): %s' % (idx, col)
tooltip = mpld3.plugins.LineLabelTooltip(lines[idx], name)
#voffset=10, hoffset=10, css=css)
mpld3.plugins.connect(f, tooltip)
mpld3.plugins.connect(f, HighlightLines(lines))
plot_and_message += mpld3.fig_to_html(f)
else:
plot_and_message += mpl2html(f)
self.fig_old = f
else:
plot_and_message += html_figure(self.fig_old)
# VALUE IS WHAT GUI LOOKS UP!!!
self.value = plot_and_message
# scatterplot
xlabel = 'GC (mean = %.1f%%)' % mean_gc
ylabel = 'Coverage (mean = %.1f)' % mean(mean_coverage)
scatter, x_pts, y_pts, labels = self.scatter(axis,
pts,
highlight_scaffold_ids,
link_scaffold_ids,
xlabel,
ylabel)
# tooltips plugin
if tooltip_plugin:
tooltip = Tooltip(scatter, labels=labels, hoffset=5, voffset=-15)
mpld3.plugins.connect(figure, tooltip)
return scatter, x_pts, y_pts, self.plot_order(labels)
text-align: right;
}
"""
labels = []
columns_to_include = ['coverage','density', 'mass', 'res dim']
frmt = lambda x: '{:.2f}'.format( x )
for i in range(len(self.peeling_trajectory['coverage'])):
label = self.peeling_trajectory.ix[[i], columns_to_include]
label.columns = ["Coverage", "Density", "Mass", "Res. Dim."]
label = label.T
label.columns = ["Box {0}".format(i)]
labels.append(str(label.to_html(float_format=frmt)))
tooltip = mpld3.plugins.PointHTMLTooltip(p, labels, voffset=10,
hoffset=10, css=css)
mpld3.plugins.connect(fig, tooltip)
return fig
import matplotlib.pyplot
import mpld3
fig, ax = matplotlib.pyplot.subplots()
ax.grid(True, alpha=0.3)
points = ax.plot(
X[:, 0], X[:, 1], "o", color="b", mec="k", ms=5, mew=1, alpha=0.6
)
ax.set_xlabel("x")
ax.set_ylabel("y")
ax.set_title("Hover mouse to reveal context", size=20)
tooltip = mpld3.plugins.PointHTMLTooltip(
points[0], contexts, voffset=10, hoffset=10
)
mpld3.plugins.connect(fig, tooltip)
mpld3.save_html(fig, file)
# # Show only desired run
# handles, labels = ax.get_legend_handles_labels() # return lines and labels
# self.logger.debug("Handles: %s", handles)
# self.logger.debug("Labels: %s", labels)
# interactive_legend = mpld3.plugins.InteractiveLegendPlugin(zip(handles,
# ax.collections),
# labels,
# alpha_unsel=0,
# alpha_over=1,
# start_visible=True)
# mpld3.plugins.connect(fig, interactive_legend)
tooltip = mpld3.plugins.PointHTMLTooltip(scatter, labels,
voffset=10, hoffset=10)#, css=self.css)
mpld3.plugins.connect(fig, tooltip)
if scatter_inc:
tooltip = mpld3.plugins.PointHTMLTooltip(scatter_inc, np.array(labels)[inc_indx].tolist(),
voffset=10, hoffset=10)#, css=self.css)
mpld3.plugins.connect(fig, tooltip)
if self.output_dir:
self.logger.debug("Save to %s", self.output_dir)
with open(self.output_dir, "w") as fp:
mpld3.save_html(fig, fp)
html = mpld3.fig_to_html(fig)
plt.close(fig)
return html
ax = fig.add_subplot(1,N_CLUSTERS+1,1)
ax.grid(True, alpha=0.3)
colors = [(random.random(), random.random(), random.random()) for x in range(N_CLUSTERS)]
for k, col in zip(range(N_CLUSTERS), colors):
my_members = k_means_labels == k
cluster_center = k_means_cluster_centers[k]
points = ax.plot(X[my_members, 0], X[my_members, 1], 'w', markerfacecolor=col, marker='.', label='Cluster %i' % k)
centers = ax.plot(cluster_center[0], cluster_center[1], 'o', markerfacecolor=col, markeredgecolor='k', markersize=6)
labels = []
for movie in movies[k_means_labels == k]:
labels.append(movie.get('Title', '') + " " + movie.get('imdbID', '') + " " + ", ".join(movie.get('Genre', '')) + " " + movie.get('', '') + " ")
tooltip = plugins.PointHTMLTooltip(points[0], labels, voffset=10, hoffset=10)
plugins.connect(fig, tooltip)
ax.set_title('KMeans')
ax.set_xticks(())
ax.set_yticks(())
ax.legend()
blah = []
for k in range(N_CLUSTERS):
innerDict = {}
for movie in movies[k_means_labels == k]:
genres = movie.get('Genre', '')
for genre in genres:
if genre in innerDict:
text-align: right;
}
"""
labels = []
columns_to_include = ['coverage','density', 'mass', 'res dim']
frmt = lambda x: '{:.2f}'.format( x )
for i in range(len(self.peeling_trajectory['coverage'])):
label = self.peeling_trajectory.ix[[i], columns_to_include].T
label.columns = ['box {0}'.format(i)]
# .to_html() is unicode; so make leading 'u' go away with str()
labels.append(str(label.to_html(float_format=frmt)))
tooltip = mpld3.plugins.PointHTMLTooltip(p, labels, voffset=10,
hoffset=10, css=css)
mpld3.plugins.connect(fig, tooltip)
return fig