Matplotlib

Using matplotlib in Jupyter notebook



In [4]:

    
import matplotlib.pyplot as plt
%matplotlib inline



In [5]:

    
import numpy as np

File Reading

Line Plots

plt.plot Plot lines and/or markers:

plot(x, y)
- plot x and y using default line style and color
plot(x, y, 'bo')
- plot x and y using blue circle markers
plot(y)
- plot y using x as index array 0..N-1
plot(y, 'r+')
- Similar, but with red plusses

run

%pdoc plt.plot

for more details



In [11]:

    
x = np.arange(-np.pi,np.pi,0.01) # Create an array of x values from -pi to pi with 0.01 interval
y = np.sin(x) # Apply sin function on all x
plt.plot(x,y)









    Out[11]:





[<matplotlib.lines.Line2D at 0x7ff37fa39a50>]



In [12]:

    
plt.plot(y)









    Out[12]:





[<matplotlib.lines.Line2D at 0x7ff37f904690>]

Scatter Plots

plt.plot can also plot markers.



In [15]:

    
x = np.arange(0,10,1)  # x = 1,2,3,4,5...
y = x*x # Squared x
plt.plot(x,y,'bo') # plot x and y using blue circle markers









    Out[15]:





[<matplotlib.lines.Line2D at 0x7ff37f84a7d0>]



In [17]:

    
plt.plot(x,y,'r+') # plot x and y using red plusses









    Out[17]:





[<matplotlib.lines.Line2D at 0x7ff37f6c3090>]

Plot properties

Add x-axis and y-axis



In [18]:

    
x = np.arange(-np.pi,np.pi,0.001)
plt.plot(x,np.sin(x))
plt.title('y = sin(x)')    # title
plt.xlabel('x (radians)')  # x-axis label
plt.ylabel('y')            # y-axis label









    Out[18]:





<matplotlib.text.Text at 0x7ff37f686e90>



In [21]:

    
# To plot the axis label in LaTex, we can run
from matplotlib import rc
## For sans-serif font:
rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})
rc('text', usetex=True)



In [20]:

    
## for Palatino and other serif fonts use:
#rc('font',**{'family':'serif','serif':['Palatino']})



In [24]:

    
plt.plot(x,np.sin(x))
plt.title(r'T = sin($\theta$)')    # title, the `r` in front of the string means raw string
plt.xlabel(r'$\theta$ (radians)')  # x-axis label, LaTex synatx should be encoded with $$
plt.ylabel('T')            # y-axis label









    Out[24]:





<matplotlib.text.Text at 0x7ff37f52db50>

Multiple plots



In [13]:

    
x1 = np.linspace(0.0, 5.0)
x2 = np.linspace(0.0, 2.0)

y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)
y2 = np.cos(2 * np.pi * x2)

plt.subplot(2, 1, 1)
plt.plot(x1, y1, '.-')
plt.title('Plot 2 graph at the same time')
plt.ylabel('Amplitude (Damped)')

plt.subplot(2, 1, 2)
plt.plot(x2, y2, '.-')
plt.xlabel('time (s)')
plt.ylabel('Amplitude (Undamped)')









    Out[13]:





<matplotlib.text.Text at 0x7f74d48ee950>

Save figure



In [30]:

    
plt.plot(x,np.sin(x))
plt.savefig('plot.pdf')
plt.savefig('plot.png')



In [31]:

    
# To load image into this Jupyter notebook
from IPython.display import Image
Image("plot.png")









    Out[31]:

AplPy



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