Lecture 13: ES 102
Plotting With Matplotlib
Introduction to Computing
IIT Gandhinagar, India
Oct, 2013
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Bireswar,Shivakumar (IIT Gandhinagar)
Lecture 13
Oct, 2013
1 / 11
Simple Plotting
Matplotlib provides the necessary functions for data visualization.
pylab is an interface to matplotlib.
Use import pylab as pl to use matplotlib.
Matplotlib is generally used in conjunction with numpy. Use import
numpy as np for that.
This lecture is based on http://scipy-lectures.github.io/
intro/matplotlib/matplotlib.html. Visit the site for more
information.
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import numpy a s np
import p y l a b a s p l
x=np . a r a n g e ( − 4 , 4 , 0 . 1 )
s = np . s i n ( x ) # s i n d e f i n e d i n math and numpy
# behaves d i f f e r e n t l y
q = x∗x # e l e m e n t−w i s e m u l t i p l i c a t i o n
pl . plot (x , s )
pl . plot (x , q)
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p l . show ( )
Bireswar,Shivakumar (IIT Gandhinagar)
Lecture 13
Oct, 2013
2 / 11
Simple Plotting
plot() generates an object that can be plotted.
show() actually draws all the plottable objects created.
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Bireswar,Shivakumar (IIT Gandhinagar)
Lecture 13
Oct, 2013
3 / 11
Customizing
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import numpy a s np
import p y l a b a s p l
x=np . l i n s p a c e (−np . p i , np . p i , 2 0 0 , e n d p o i n t=True )
s = np . s i n ( x )
c = np . c o s ( x )
p l . p l o t ( x , s , c o l o r=’ red ’ , l i n e w i d t h =1 , l i n e s t y l e =’ -- ’ , l a b e l=" sine " )
p l . p l o t ( x , c , c o l o r=’ blue ’ , l i n e w i d t h = 1 . 5 , l i n e s t y l e =’ - ’ , l a b e l=" cosine " )
p l . l e g e n d ( l o c=’ upper right ’ )
p l . show ( )
linspace(start,end,no of elms,endpoint=True/False):
generate no of elms many equally spaced elements from start to
end. end will not be included only if endpoint=False.
color color of the curve;linewidth thickness of the
curve;linestyle curve pattern; label set the name of the curve.
legend where to show the names of the curves.
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Bireswar,Shivakumar (IIT Gandhinagar)
Lecture 13
Oct, 2013
4 / 11
Customizing: Axes Limit, Ticks and Grid
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import numpy a s np
import p y l a b a s p l
x=np . l i n s p a c e (−2∗np . p i , 2 ∗ np . p i , 2 0 0 , e n d p o i n t=True )
s = np . s i n ( x )
p l . p l o t ( x , s , c o l o r=’ green ’ , l i n e w i d t h =1 , l i n e s t y l e =’ - ’ )
p l . x l i m ( x . min ( ) ∗ 1 . 1 , x . max ( ) ∗ 1 . 1 )
p l . ylim ( −1.1 ,1.1)
p l . x t i c k s ([−2∗ np . p i , −np . p i , 0 , np . p i , 2∗np . p i ] )
p l . y t i c k s ([ −1 , 0 , +1])
p l . g r i d ( True )
p l . show ( )
xlim sets x-axis limit, ylim sets y-axis limit.
xticks,yticks puts the ticks in the axes.
grid sets a rectangular grid.
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Bireswar,Shivakumar (IIT Gandhinagar)
Lecture 13
Oct, 2013
5 / 11
Customizing: Changing Axes
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import numpy a s np
import p y l a b a s p l
x=np . l i n s p a c e (−2∗np . p i , 2 ∗ np . p i , 2 0 0 , e n d p o i n t=True )
ax = p l . gc a ( ) # gca s t a n d s f o r ’ g e t c u r r e n t a x i s ’
ax . s p i n e s [ ’ right ’ ] . s e t c o l o r ( ’ none ’ )
# No c o l o r
ax . s p i n e s [ ’ top ’ ] . s e t c o l o r ( ’ none ’ )
# No c o l o r
ax . x a x i s . s e t t i c k s p o s i t i o n ( ’ bottom ’ )
# Where t o
ax . s p i n e s [ ’ bottom ’ ] . s e t p o s i t i o n ( ( ’ data ’ , 0 ) ) # s e t
ax . y a x i s . s e t t i c k s p o s i t i o n ( ’ left ’ )
# Where t o
ax . s p i n e s [ ’ left ’ ] . s e t p o s i t i o n ( ( ’ data ’ , 0 ) )
# set
put
the
put
the
the t i c k s
bottom l i n e t o 0 i n data−s p a c e
the t i c k s
l e f t l i n e t o 0 i n data−s p a c e
s = np . s i n ( x )
p l . p l o t ( x , s , c o l o r=’ green ’ , l i n e w i d t h =1 , l i n e s t y l e =’ - ’ )
p l . show ( )
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Bireswar,Shivakumar (IIT Gandhinagar)
Lecture 13
Oct, 2013
6 / 11
More Customizing
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import numpy a s np
import p y l a b a s p l
x=np . l i n s p a c e (−2∗np . p i , 2 ∗ np . p i , 2 0 0 , e n d p o i n t=True )
s = np . s i n ( x )
p l . p l o t ( x , s , c o l o r=’ green ’ , l i n e w i d t h =1 , l i n e s t y l e =’ - ’ )
p l . x t i c k s ([−2∗ np . p i , −np . p i , 0 , np . p i , 2∗np . p i ] ,
[ r ’$ -2\ pi$ ’ , r ’$ \ pi$ ’ , r ’ $0$ ’ , r ’$ \ pi$ ’ , r ’ $2 \ pi$ ’ ] )
p l . y t i c k s ([ −1 , 0 , +1])
p l . show ( )
We can embed some LATEXcode in the program to get fancy fonts.
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Bireswar,Shivakumar (IIT Gandhinagar)
Lecture 13
Oct, 2013
7 / 11
Bar Plot
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import numpy a s np
import p y l a b a s p l
x=np . a r r a y ( [ 0 , 1 , 2 , 3 , 4 , 5 ] )
y=np . a r r a y ( [ 5 , 6 , 2 , 1 3 , 4 , 9 ] )
z=np . random . r a n d ( 6 ) ∗ 1 0
p l . b a r ( x , y , f a c e c o l o r=’ red ’ , e d g e c o l o r=’ white ’ )
p l . b a r ( x , −z , f a c e c o l o r=’ blue ’ , e d g e c o l o r=’ white ’ )
p l . show ( )
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Bireswar,Shivakumar (IIT Gandhinagar)
Lecture 13
Oct, 2013
8 / 11
Scatter Plot
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import numpy a s np
import p y l a b a s p l
r 1=np . random . r a n d ( 1 0 0 0 )
x=( r1 −0.5)∗10
r 2=np . random . r a n d ( 1 0 0 0 )
y=10∗ r 2
pl . scatter (x , y)
p l . show ( )
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Bireswar,Shivakumar (IIT Gandhinagar)
Lecture 13
Oct, 2013
9 / 11
Polar Plot
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import p y l a b a s p l
import numpy a s np
ax = p l . a x e s ( p o l a r=True ) # Only c h a n g e HERE
N = 200
t h e t a = np . a r a n g e ( 0 . 0 , 2 ∗ np . p i , 2 ∗ np . p i / N)
r a d i i = 10 ∗ np . s i n ( t h e t a )
p l . p l o t ( t h e t a , r a d i i , c o l o r=’ red ’ )
p l . p l o t ( theta ,5∗ t h e t a )
p l . show ( )
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Bireswar,Shivakumar (IIT Gandhinagar)
Lecture 13
Oct, 2013
10 / 11
Plotting Data from File
In many situations the data to be plotted is in a file.
You can read the data, store it in arrays and plot the data.
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import numpy a s np
import p y l a b a s p l
d a t a f i l e = open ( " data . txt " , " r " )
x =[]
y =[]
for l i n e in d a t a f i l e :
temp= l i n e . s p l i t ( )
p= f l o a t ( temp [ 0 ] )
q= f l o a t ( temp [ 1 ] )
x+=[p ]
y+=[q ]
X=np . a r r a y ( x )
Y=np . a r r a y ( y )
p l . p l o t (X , Y , c o l o r=’ green ’ , l i n e w i d t h =1 , l i n e s t y l e =’ - ’ )
p l . show ( )
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Bireswar,Shivakumar (IIT Gandhinagar)
Lecture 13
Oct, 2013
11 / 11