def figure_to_vdom_image(figure):
buf = io.BytesIO()
figure.savefig(buf, format='png')
buf.seek(0)
string = base64.b64encode(buf.read())
return vdomh.div(vdomh.img(src='data:image/png;base64,' +
urllib.parse.quote(string)),
style={"display": "inline-block"})
def fig2vdom(fig, **kwargs):
"""Convert a matplotlib figure to an online image
"""
buf = io.BytesIO()
fig.savefig(buf, format='png', bbox_inches='tight')
buf.seek(0)
string = base64.b64encode(buf.read())
plt.close()
return img(src='data:image/png;base64,' + urllib.parse.quote(string),
**kwargs)
async def get_dashboard():
example = div(
span(img(src=image_url, style=dict(width='100', heigth='100')),
h1('Smart 311 Dashboard')),
p('Written in Python, 100%'),
topten(),
p('Top ten complaint types'),
).to_html()
return HTMLResponse(content=example)
def cache_fig(fig, output_dir, url_dir, k, width=840, cache=True):
import plotnine
output_file = os.path.join(output_dir, k + ".png")
output_file_url = os.path.join(url_dir, k + ".png")
if not (os.path.exists(output_file) and cache):
if isinstance(fig, plotnine.ggplot):
fig.save(output_file)
else:
fig.savefig(output_file)
return img(src=output_file_url, width=width)
def topten():
fig, ax = plt.subplots()
df['complaint_type'].value_counts().head(10).plot(kind='barh', ax=ax)
plt.tight_layout()
buf = io.BytesIO()
fig.savefig(buf, format='png')
buf.seek(0)
string = base64.b64encode(buf.read())
plt.close()
return img(src='data:image/png;base64,' + urllib.parse.quote(string))
def template_vdom_pattern(name,
n_seqlets,
trimmed_motif,
full_motif,
figures_url,
add_plots={},
metacluster=""):
return details(
summary(
name,
f": # seqlets: {n_seqlets}",
# br(),
trimmed_motif), # ", rc: ", motif_rc),
details(
summary("Aggregated profiles and contribution scores)"),
img(src=figures_url + "/agg_profile_contribcores.png", width=840),
),
details(
summary("Aggregated hypothetical contribution scores)"),
img(src=figures_url + "/agg_profile_hypcontribscores.png",
width=840),
),
details(
summary("Sequence"),
full_motif,
br(),
img(src=figures_url + "/heatmap_seq.png", width=840 // 2),
),
details(
summary("ChIP-nexus counts"),
img(src=figures_url + "/profile_aggregated.png", width=840),
img(src=figures_url + "/profile_heatmap.png", width=840),
),
details(
summary("Importance scores (profile)"),
img(src=figures_url + "/contrib_profile.png", width=840),
),
details(
summary("Importance scores (counts)"),
img(src=figures_url + "/contrib_counts.png", width=840),
),
*[details(summary(k), *v) for k, v in add_plots.items()],
id=metacluster + "/" + name)
def dashboard():
return div(
span(img(src=image_url, style=dict(width='100', heigth='100')),
h1('Smart 311 Dashboard')), img(width='400', src=barplot_url),
p('Written in Python, 100%'))
from IPython.display import display
from vdom.helpers import h1, p, img, div, b
display(
div(
h1('Our Incredibly Declarative Example'),
p('Can you believe we wrote this ', b('in Python'), '?'),
img(src="https://media.giphy.com/media/xUPGcguWZHRC2HyBRS/giphy.gif"),
p('What will ', b('you'), ' create next?'),
))