##// END OF EJS Templates
Inherit history machinery from LoggingConfigurable...
Inherit history machinery from LoggingConfigurable HistoryManager uses log (in an error case, which is why we didn't spot it before). Closes gh-9351

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/ examples / IPython Kernel / Working With External Code.ipynb

Working With External Code¶

The IPython Kernel makes it easy to incorporate external code from sources such as the internet or copy/paste.

Pasting code into cells¶

You can copy and paste code from other sources directly into cells. Pasting code with >>> prompts works as expected:

In [1]:
>>> the_world_is_flat = 1
>>> if the_world_is_flat:
...     print("Be careful not to fall off!")
Be careful not to fall off!

The %load magic¶

The %load magic lets you load code from URLs or local files:

In [2]:
%load?
In [3]:
%matplotlib inline
In [ ]:
%load http://matplotlib.org/mpl_examples/showcase/integral_demo.py
In [4]:
# %load http://matplotlib.org/mpl_examples/showcase/integral_demo.py
"""
Plot demonstrating the integral as the area under a curve.

Although this is a simple example, it demonstrates some important tweaks:

    * A simple line plot with custom color and line width.
    * A shaded region created using a Polygon patch.
    * A text label with mathtext rendering.
    * figtext calls to label the x- and y-axes.
    * Use of axis spines to hide the top and right spines.
    * Custom tick placement and labels.
"""
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon


def func(x):
    return (x - 3) * (x - 5) * (x - 7) + 85


a, b = 2, 9 # integral limits
x = np.linspace(0, 10)
y = func(x)

fig, ax = plt.subplots()
plt.plot(x, y, 'r', linewidth=2)
plt.ylim(ymin=0)

# Make the shaded region
ix = np.linspace(a, b)
iy = func(ix)
verts = [(a, 0)] + list(zip(ix, iy)) + [(b, 0)]
poly = Polygon(verts, facecolor='0.9', edgecolor='0.5')
ax.add_patch(poly)

plt.text(0.5 * (a + b), 30, r"$\int_a^b f(x)\mathrm{d}x$",
         horizontalalignment='center', fontsize=20)

plt.figtext(0.9, 0.05, '$x$')
plt.figtext(0.1, 0.9, '$y$')

ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
ax.xaxis.set_ticks_position('bottom')

ax.set_xticks((a, b))
ax.set_xticklabels(('$a$', '$b$'))
ax.set_yticks([])

plt.show()
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