Difference between revisions of "CompSciHW5"
From Predictive Chemistry
| (2 intermediate revisions by the same user not shown) | |||
| Line 7: | Line 7: | ||
c) h(x) = exp(-x*x/(2*sigma)), for sigma = 1, 2, and 3 |
c) h(x) = exp(-x*x/(2*sigma)), for sigma = 1, 2, and 3 |
||
d) w(x) = g(x) - 4*g(x-2.0) |
d) w(x) = g(x) - 4*g(x-2.0) |
||
| + | e) u(x, y) = sin(x)*cos(3*y) - cos(2*x)*sin(y) [Hint: use pylab.imshow()] |
||
2) Name the type of the following functions: |
2) Name the type of the following functions: |
||
| Line 18: | Line 19: | ||
d) def chaos(*a, **b): |
d) def chaos(*a, **b): |
||
return random.random()*random.random() |
return random.random()*random.random() |
||
| + | e) def sliceof(st, stop, step, *a): |
||
| + | return a[st:stop:step] |
||
</pre> |
</pre> |
||
| + | |||
| + | Hint: Try defining x as an array of x-values, and f,g,h, etc. as a python function with type float -> float. |
||
| + | Then plot(x, f(x)) |
||
| + | or calculate the values using vals = map(f, x) |
||
| + | The first one tricks the function into the type (array -> array), and the second computes 1 float at a time. |
||
| + | |||
| + | <source lang="python"> |
||
| + | import numpy as np |
||
| + | from pylab import plot, show, imshow |
||
| + | N = 100 |
||
| + | x = np.linspace(-3.0, 3.0, N) # plotting 1D functions |
||
| + | y = np.linspace(-2.0, 2.0, N) |
||
| + | |||
| + | X, Y = np.meshgrid(x, y) # plotting 2D functions (1.e) |
||
| + | </source> |
||
Latest revision as of 14:47, 4 March 2016
Homework 5 - Due Friday, March 4, 2016
1) Use numpy and pyplot to plot the following functions:
(remember to start by choosing an appropriate range for x)
a) f(x) = sin(x) cos(2x)
b) g(x) = x (if x is in 0,1), 2-x (if x is in 1,2), 0 otherwise
c) h(x) = exp(-x*x/(2*sigma)), for sigma = 1, 2, and 3
d) w(x) = g(x) - 4*g(x-2.0)
e) u(x, y) = sin(x)*cos(3*y) - cos(2*x)*sin(y) [Hint: use pylab.imshow()]
2) Name the type of the following functions:
(remember that *a means a list is input and **a means a dictionary)
a) def joinwith(space, *a):
return space.join(a)
b) def map_on_n(f, n):
return [f(i) for i in range(n)]
c) def get_elem(k="default", **d):
return d[k] + 2.0
d) def chaos(*a, **b):
return random.random()*random.random()
e) def sliceof(st, stop, step, *a):
return a[st:stop:step]
Hint: Try defining x as an array of x-values, and f,g,h, etc. as a python function with type float -> float. Then plot(x, f(x)) or calculate the values using vals = map(f, x) The first one tricks the function into the type (array -> array), and the second computes 1 float at a time.
<source lang="python"> import numpy as np from pylab import plot, show, imshow N = 100 x = np.linspace(-3.0, 3.0, N) # plotting 1D functions y = np.linspace(-2.0, 2.0, N)
X, Y = np.meshgrid(x, y) # plotting 2D functions (1.e) </source>
