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Add purging of client result cache to parallel.Client...
Add purging of client result cache to parallel.Client The new methods clear the cached values and free some memory. The whole thing is split into different methods to both clear the client and the hub side. Additionally fix some bugs in other parts of the code.

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trapezoid_rule.ipynb
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Basic numerical integration: the trapezoid rule

A simple illustration of the trapezoid rule for definite integration:

$$ \int_{a}^{b} f(x)\, dx \approx \frac{1}{2} \sum_{k=1}^{N} \left( x_{k} - x_{k-1} \right) \left( f(x_{k}) + f(x_{k-1}) \right). $$
First, we define a simple function and sample it between 0 and 10 at 200 points
In [1]:
%pylab inline
Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].
For more information, type 'help(pylab)'.
In [2]:
def f(x):
    return (x-3)*(x-5)*(x-7)+85

x = linspace(0, 10, 200)
y = f(x)

Choose a region to integrate over and take only a few points in that region

In [3]:
a, b = 1, 9
xint = x[logical_and(x>=a, x<=b)][::30]
yint = y[logical_and(x>=a, x<=b)][::30]

Plot both the function and the area below it in the trapezoid approximation

In [4]:
plot(x, y, lw=2)
axis([0, 10, 0, 140])
fill_between(xint, 0, yint, facecolor='gray', alpha=0.4)
text(0.5 * (a + b), 30,r"$\int_a^b f(x)dx$", horizontalalignment='center', fontsize=20);
No description has been provided for this image

Compute the integral both at high accuracy and with the trapezoid approximation

In [5]:
from scipy.integrate import quad, trapz
integral, error = quad(f, 1, 9)
print "The integral is:", integral, "+/-", error
print "The trapezoid approximation with", len(xint), "points is:", trapz(yint, xint)
The integral is: 680.0 +/- 7.54951656745e-12
The trapezoid approximation with 6 points is: 621.286411141
In [ ]: