Plot / Matplotlib

Use matplotlib to create plots. Also demonstrates how to provide live control over plots.

import uuid
import os
import numpy as np
import matplotlib.pyplot as plt
from h2o_wave import ui, main, app, Q
np.random.seed(19680801)
@app('/demo')
async def serve(q: Q):
if not q.client.initialized: # First visit
q.client.initialized = True
q.client.points = 25
q.client.alpha = 50
q.page['controls'] = ui.form_card(
box='1 1 2 3',
items=[
ui.text_xl("Lets make some plots"),
ui.slider(name='points', label='Points', min=5, max=50, step=1, value=q.client.points, trigger=True),
ui.slider(name='alpha', label='Alpha', min=5, max=100, step=1, value=q.client.alpha, trigger=True),
]
)
q.page['plot'] = ui.markdown_card(box='3 1 2 3', title='Your plot!', content='')
if q.args.points is not None:
q.client.points = q.args.points
if q.args.alpha is not None:
q.client.alpha = q.args.alpha
n = q.client.points
# Render plot
plt.figure(figsize=(2, 2))
plt.scatter(
np.random.rand(n), np.random.rand(n),
s=(30 * np.random.rand(n)) ** 2,
c=np.random.rand(n),
alpha=q.client.alpha / 100.0
)
image_filename = f'{str(uuid.uuid4())}.png'
plt.savefig(image_filename)
# Upload
image_path, = await q.site.upload([image_filename])
# Clean up
os.remove(image_filename)
# Display our plot in our markdown card
q.page['plot'].content = f'![plot]({image_path})'
# Save page
await q.page.save()

Tags: โ€‚matplotlib โ€‚plot