Ipympl¶
Imports¶
import numpy as np
import scipy as sp
import matplotlib as plt
import matplotlib.pyplot as plt
from ipywidgets import interact, interactive, fixed
import ipywidgets as widgets
# seed the random number generator so we all get the same results
np.random.seed(17)
# some nice colors from http://colorbrewer2.org/
COLOR1 = '#7fc97f'
COLOR2 = '#beaed4'
COLOR3 = '#fdc086'
COLOR4 = '#ffff99'
COLOR5 = '#386cb0'
%matplotlib widget
Testing ipympl¶
# Testing matplotlib interactions with a simple plot
fig = plt.figure()
plt.plot(np.sin(np.linspace(0, 20, 100)));
fig.canvas.toolbar_visible = False
fig.canvas.header_visible = False
fig.canvas.footer_visible = False
fig.canvas.resizable = False
fig.canvas.capture_scroll = True
fig.canvas.toolbar_visible = True
display(fig.canvas)
3d plot¶
from mpl_toolkits.mplot3d import axes3d
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
# Grab some test data.
X, Y, Z = axes3d.get_test_data(0.05)
# Plot a basic wireframe.
ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)
plt.show()
Subplots¶
# A more complex example from the matplotlib gallery
np.random.seed(0)
n_bins = 10
x = np.random.randn(1000, 3)
fig, axes = plt.subplots(nrows=2, ncols=2)
ax0, ax1, ax2, ax3 = axes.flatten()
colors = ['red', 'tan', 'lime']
ax0.hist(x, n_bins, density=1, histtype='bar', color=colors, label=colors)
ax0.legend(prop={'size': 10})
ax0.set_title('bars with legend')
ax1.hist(x, n_bins, density=1, histtype='bar', stacked=True)
ax1.set_title('stacked bar')
ax2.hist(x, n_bins, histtype='step', stacked=True, fill=False)
ax2.set_title('stack step (unfilled)')
# Make a multiple-histogram of data-sets with different length.
x_multi = [np.random.randn(n) for n in [10000, 5000, 2000]]
ax3.hist(x_multi, n_bins, histtype='bar')
ax3.set_title('different sample sizes')
fig.tight_layout()
plt.show()
fig.canvas.toolbar_position = 'right'
# fig.canvas.toolbar_position = 'right'
Interactive Mode¶
# ensure we are interactive mode
# this is default but if this notebook is executed out of order it may have been turned off
plt.ion()
fig = plt.figure()
ax = fig.gca()
ax.imshow(Z)
<matplotlib.image.AxesImage at 0x7fb5117e7ca0>
widgets.AppLayout(
center=fig.canvas,
footer=widgets.Button(icon='check'),
pane_heights=[0, 6, 1]
)
# Fixes Double Display
plt.ioff()
fig = plt.figure()
plt.ion()
ax = fig.gca()
ax.imshow(Z)
widgets.AppLayout(
center=fig.canvas,
footer=widgets.Button(icon='check'),
pane_heights=[0, 6, 1]
)
# Fixing Double Display
out = widgets.Output()
with out:
fig = plt.figure()
ax = fig.gca()
ax.imshow(Z)
widgets.AppLayout(
center=out,
footer=widgets.Button(icon='check'),
pane_heights=[0, 6, 1]
)