# Interact Exercise 2

## Imports



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




:0: FutureWarning: IPython widgets are experimental and may change in the future.



## Plotting with parameters

Write a plot_sin1(a, b) function that plots $sin(ax+b)$ over the interval $[0,4\pi]$.

• Customize your visualization to make it effective and beautiful.
• Customize the box, grid, spines and ticks to match the requirements of this data.
• Use enough points along the x-axis to get a smooth plot.
• For the x-axis tick locations use integer multiples of $\pi$.
• For the x-axis tick labels use multiples of pi using LaTeX: $3\pi$.


In [3]:

def plot_sine1(a,b):
#style graph
plt.figure(figsize=(10,5))
plt.rc('xtick', labelsize=14)
plt.rc('ytick', labelsize=12)
ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')

#Set X(input array) and Y(output array)
x = np.linspace(0.0, 4*np.pi, 500)
y = np.sin(a*x+b)

#Label Axis/ Set Ticks
plt.xlabel("X", fontsize = 14)
plt.ylabel("Y", fontsize = 14)
plt.title("y(x) = sin(%sx + %s)" %(a, b), fontsize=16)
plt.xticks(np.linspace(0.0, 4*np.pi, 5), [r'$0$', r'$\pi$', r'$2\pi$', r'$3\pi$', r'$4\pi$'])
plt.plot(x, y)




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]:

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:

• dashed red: r--
• blue circles: bo
• dotted black: k.

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 [10]:

def plot_sine2(a, b, style='b-'):
#Style Graph
plt.figure(figsize=(10,5))
plt.rc('xtick', labelsize=14)
plt.rc('ytick', labelsize=12)
ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')

#Set x(input array) and y(output array)
x = np.linspace(0.0, 4*np.pi, 500)
y = np.sin(a*x+b)

#More styling (Labels)
plt.xlabel("X", fontsize = 14)
plt.ylabel("Y", fontsize = 14)
plt.title("y(x) = sin(%sx + %s)" %(a, b), fontsize=16)
plt.xticks(np.linspace(0.0, 4*np.pi, 5), [r'$0$', r'$\pi$', r'$2\pi$', r'$3\pi$', r'$4\pi$'])

# Now we include a style argument!
plt.plot(x, y, style)




In [11]:

plot_sine2(4.0, -1.0, 'b-')






Use interact to create a UI for plot_sine2.

• Use a slider for a and b as above.
• Use a drop down menu for selecting the line style between a dotted blue line line, black circles and red triangles.


In [13]:

interact(plot_sine2, a=(0.0,5.0,0.1), b=(-5.0,5.0,0.1), style= {"blue dotted line": 'b.', "black circles": 'ko', "red triangles": 'r^'});







In [84]:

assert True # leave this for grading the plot_sine2 exercise



Used "Lev Levitsky"'s idea from StackOverFlow to set tick numbers

Used "unutbu"'s method for using latex in matplotlib



In [ ]: