In [1]:
%matplotlib inline
from matplotlib import pyplot as plt
import numpy as np
In [2]:
from IPython.html.widgets import interact, interactive, fixed
from IPython.display import display
Write a plot_sin1(a, b) function that plots $sin(ax+b)$ over the interval $[0,4\pi]$.
$3\pi$.
In [3]:
# YOUR CODE HERE
def plot_sine1(a, b):
x = np.arange(0, 4*np.pi, 0.1)
v = np.sin(a*x+b)
plt.plot(v)
In [4]:
plot_sine1(5, 3.4)
Then use interact to create a user interface for exploring your function:
a should be a floating point slider over the interval $[0.0,5.0]$ with steps of $0.1$.b should be a floating point slider over the interval $[-5.0,5.0]$ with steps of $0.1$.
In [5]:
# YOUR CODE HERE
interact(plot_sine1, a=[0.0, 5.0, 0.1], b=[-5.0, 5.0, 0.1]);
In [6]:
assert True # leave this for grading the plot_sine1 exercise
In matplotlib, the line style and color can be set with a third argument to plot. Examples of this argument:
r--bok.Write a plot_sine2(a, b, style) function that has a third style argument that allows you to set the line style of the plot. The style should default to a blue line.
In [7]:
# YOUR CODE HERE
def plot_sine2(a, b, style):
x = np.arange(0, 4*np.pi, 0.1)
v = np.sin(a*x+b)
return plt.plot(v, style)
In [8]:
plot_sine2(4.0, -1.0, 'r--')
Out[8]:
Use interact to create a UI for plot_sine2.
a and b as above.
In [12]:
# YOUR CODE HERE
interact(plot_sine2, a=[0.0, 5.0, 0.1], b=[-5.0, 5.0, 0.1],
style={'black circles':'ko', 'red triangles':'r^', 'blue dots':'b.'})
In [10]:
assert True # leave this for grading the plot_sine2 exercise