Aug
SEP
Oct
08
2019
2020
2021
About this capture
T h e W a y b a c k M a c h i n e - h t t p : / / w e b . a r c h i v e . o r g / w e b / 2 0 2 0 0 9 0 8 0 8 4 0 1 4 / h t t p s : / / g i t h u b . c o m / r o u g i e r / m a t p l o t l i b - t u t o r i a l
S k i p t o c o n t e n t
/ ; r e f _ c t a : S i g n u p ; r e f _ l o c : h e a d e r l o g g e d o u t " >
S i g n up
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F e a t u r e s → ● C o d e r e v i e w ● P r o j e c t m a n a g e m e n t ● I n t e g r a t i o n s ● A c t i o n s ● P a c k a g e s ● S e c u r i t y ● T e a m m a n a g e m e n t ● H o s t i n g ● M o b i l e
● C u s t o m e r s t o r i e s → ● S e c u r i t y →
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● E x p l o r e G i t H u b →
L e a r n & c o n t r i b u t e ● T o p i c s ● C o l l e c t i o n s ● T r e n d i n g ● L e a r n i n g L a b ● O p e n s o u r c e g u i d e s
C o n n e c t w i t h o t h e r s ● E v e n t s ● C o m m u n i t y f o r u m ● G i t H u b E d u c a t i o n ● G i t H u b S t a r s p r o g r a m
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P l a n s → ● C o m p a r e p l a n s ● C o n t a c t S a l e s
● N o n p r o f i t → ● E d u c a t i o n →
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{ { m e s s a g e } }
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W a t c h
1 0 3
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S t a r
1 . 6 k
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F o r k
5 6 8
M a t p l o t l i b t u t o r i a l f o r b e g i n n e r
1 . 6 k s t a r s
5 6 8 f o r k s
S t a r
W a t c h
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C o d e ●
I s s u e s 6 ●
P u l l r e q u e s t s 0 ●
A c t i o n s ●
P r o j e c t s 0 ●
S e c u r i t y ●
I n s i g h t s
M o r e
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C o d e
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I s s u e s
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P u l l r e q u e s t s
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A c t i o n s
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P r o j e c t s
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S e c u r i t y
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I n s i g h t s
D i s m i s s
J o i n G i t H u b t o d a y G i t H u b i s h o m e t o o v e r 5 0 m i l l i o n d e v e l o p e r s w o r k i n g t o g e t h e r t o h o s t a n d r e v i e w c o d e , m a n a g e p r o j e c t s , a n d b u i l d s o f t w a r e t o g e t h e r .
S i g n u p
1 b r a n c h
1 t a g
G o t o f i l e
C o d e
C l o n e w i t h H T T P S
U s e G i t o r c h e c k o u t w i t h S V N u s i n g t h e w e b U R L .
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O p e n w i t h G i t H u b D e s k t o p
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D o w n l o a d Z I P
L a u n c h i n g G i t H u b D e s k t o p I f n o t h i n g h a p p e n s , d o w n l o a d G i t H u b D e s k t o p a n d t r y a g a i n .
G o b a c k
L a u n c h i n g G i t H u b D e s k t o p I f n o t h i n g h a p p e n s , d o w n l o a d G i t H u b D e s k t o p a n d t r y a g a i n .
G o b a c k
L a u n c h i n g X c o d e I f n o t h i n g h a p p e n s , d o w n l o a d X c o d e a n d t r y a g a i n .
G o b a c k
L a u n c h i n g V i s u a l S t u d i o I f n o t h i n g h a p p e n s , d o w n l o a d t h e G i t H u b e x t e n s i o n f o r V i s u a l S t u d i o a n d t r y a g a i n .
G o b a c k
L a t e s t c o m m i t
r o u g i e r
M e r g e p u l l r e q u e s t # 1 5 f r o m F r a n k l i n C h e n / f i x - p r i n t
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5 2 9 a 2 0 3
J u n 1 5 , 2 0 2 0
M e r g e p u l l r e q u e s t # 1 5 f r o m F r a n k l i n C h e n / f i x - p r i n t
Fix print function calls by adding parentheses.
5 2 9 a 2 0 3
G i t s t a t s ●
38 c o m m i t s
F i l e s
P e r m a l i n k
F a i l e d t o l o a d l a t e s t c o m m i t i n f o r m a t i o n .
T y p e N a m e L a t e s t c o m m i t m e s s a g e C o m m i t t i m e
f i g u r e s
C h a n g e d r a w i n g o r d e r
J u n 1 6 , 2 0 1 7
s c r i p t s
F i x p r i n t f u n c t i o n c a l l s b y a d d i n g p a r e n t h e s e s .
J u n 1 2 , 2 0 2 0
. g i t i g n o r e
I n i t i a l i m p o r t
M a y 1 2 , 2 0 1 3
M a k e f i l e
I n i t i a l i m p o r t
M a y 1 2 , 2 0 1 3
R E A D M E . h t m l
r e m o v e d p y l a b r e f e r e n c e
J u n 3 , 2 0 2 0
R E A D M E . r s t
r e m o v e d p y l a b r e f e r e n c e
J u n 3 , 2 0 2 0
d a n a . c s s
I n i t i a l i m p o r t
M a y 1 2 , 2 0 1 3
r e s e t . c s s
I n i t i a l i m p o r t
M a y 1 2 , 2 0 1 3
V i e w c o d e
R E A D M E . r s t
M a t p l o t l i b t u t o r i a l N i c o l a s P . R o u g i e r T a b l e o f C o n t e n t s ● I n t r o d u c t i o n ● S i m p l e p l o t ● F i g u r e s , S u b p l o t s , A x e s a n d T i c k s ● A n i m a t i o n ● O t h e r T y p e s o f P l o t s ● B e y o n d t h i s t u t o r i a l ● Q u i c k r e f e r e n c e s S o u r c e s a r e a v a i l a b l e f r o m
g i t h u b A l l c o d e a n d m a t e r i a l i s l i c e n s e d u n d e r a C r e a t i v e C o m m o n s
A t t r i b u t i o n - S h a r e A l i k e 4 . 0 . Y o u c a n t e s t y o u r i n s t a l l a t i o n b e f o r e t h e t u t o r i a l u s i n g t h e c h e c k - i n s t a l l a t i o n . p y s c r i p t . S e e a l s o : ● F r o m P y t h o n t o N u m p y ● 1 0 0 N u m p y e x e r c i c e s ● T e n s i m p l e r u l e s f o r b e t t e r f i g u r e s m a t p l o t l i b i s p r o b a b l y t h e s i n g l e m o s t u s e d P y t h o n p a c k a g e f o r 2 D - g r a p h i c s . I t
p r o v i d e s b o t h a v e r y q u i c k w a y t o v i s u a l i z e d a t a f r o m P y t h o n a n d
p u b l i c a t i o n - q u a l i t y f i g u r e s i n m a n y f o r m a t s . W e a r e g o i n g t o e x p l o r e
m a t p l o t l i b i n i n t e r a c t i v e m o d e c o v e r i n g m o s t c o m m o n c a s e s . I P y t h o n a n d t h e p y l a b m o d e I P y t h o n i s a n e n h a n c e d i n t e r a c t i v e P y t h o n s h e l l t h a t
h a s l o t s o f i n t e r e s t i n g f e a t u r e s i n c l u d i n g n a m e d i n p u t s a n d o u t p u t s , a c c e s s t o
s h e l l c o m m a n d s , i m p r o v e d d e b u g g i n g a n d m u c h m o r e . W h e n w e s t a r t i t w i t h t h e
c o m m a n d l i n e a r g u m e n t - p y l a b ( - - p y l a b s i n c e I P y t h o n v e r s i o n 0 . 1 2 ) , i t a l l o w s
i n t e r a c t i v e m a t p l o t l i b s e s s i o n s t h a t h a v e M a t l a b / M a t h e m a t i c a - l i k e f u n c t i o n a l i t y . p y p l o t p y p l o t p r o v i d e s a c o n v e n i e n t i n t e r f a c e t o t h e m a t p l o t l i b o b j e c t - o r i e n t e d
p l o t t i n g l i b r a r y . I t i s m o d e l e d c l o s e l y a f t e r M a t l a b ( TM ) . T h e r e f o r e , t h e
m a j o r i t y o f p l o t t i n g c o m m a n d s i n p y p l o t h a v e M a t l a b ( TM ) a n a l o g s w i t h s i m i l a r
a r g u m e n t s . I m p o r t a n t c o m m a n d s a r e e x p l a i n e d w i t h i n t e r a c t i v e e x a m p l e s . I n t h i s s e c t i o n , w e w a n t t o d r a w t h e c o s i n e a n d s i n e f u n c t i o n s o n t h e s a m e
p l o t . S t a r t i n g f r o m t h e d e f a u l t s e t t i n g s , w e ' l l e n r i c h t h e f i g u r e s t e p b y s t e p
t o m a k e i t n i c e r . T h e f i r s t s t e p i s t o g e t t h e d a t a f o r t h e s i n e a n d c o s i n e f u n c t i o n s :
import numpy as np
X = np.linspace(-np.pi, np.pi, 256, endpoint=True)
C, S = np.cos(X ), np.sin(X )
X i s n o w a N u m P y a r r a y w i t h 2 5 6 v a l u e s r a n g i n g f r o m - π t o + π ( i n c l u d e d ) . C i s
t h e c o s i n e ( 2 5 6 v a l u e s ) a n d S i s t h e s i n e ( 2 5 6 v a l u e s ) . T o r u n t h e e x a m p l e , y o u c a n d o w n l o a d e a c h o f t h e e x a m p l e s a n d r u n i t u s i n g :
$ python exercice_1.py
Y o u c a n g e t s o u r c e f o r e a c h s t e p b y c l i c k i n g o n t h e c o r r e s p o n d i n g f i g u r e . U s i n g d e f a u l t s D o c u m e n t a t i o n ● p l o t t u t o r i a l ● p l o t ( ) c o m m a n d M a t p l o t l i b c o m e s w i t h a s e t o f d e f a u l t s e t t i n g s t h a t a l l o w c u s t o m i z i n g a l l
k i n d s o f p r o p e r t i e s . Y o u c a n c o n t r o l t h e d e f a u l t s o f a l m o s t e v e r y p r o p e r t y i n
m a t p l o t l i b : f i g u r e s i z e a n d d p i , l i n e w i d t h , c o l o r a n d s t y l e , a x e s , a x i s a n d
g r i d p r o p e r t i e s , t e x t a n d f o n t p r o p e r t i e s a n d s o o n . W h i l e m a t p l o t l i b d e f a u l t s
a r e r a t h e r g o o d i n m o s t c a s e s , y o u m a y w a n t t o m o d i f y s o m e p r o p e r t i e s f o r
s p e c i f i c c a s e s . I n s t a n t i a t i n g d e f a u l t s D o c u m e n t a t i o n ● C u s t o m i z i n g m a t p l o t l i b I n t h e s c r i p t b e l o w , w e ' v e i n s t a n t i a t e d ( a n d c o m m e n t e d ) a l l t h e f i g u r e s e t t i n g s
t h a t i n f l u e n c e t h e a p p e a r a n c e o f t h e p l o t . T h e s e t t i n g s h a v e b e e n e x p l i c i t l y
s e t t o t h e i r d e f a u l t v a l u e s , b u t n o w y o u c a n i n t e r a c t i v e l y p l a y w i t h t h e v a l u e s
t o e x p l o r e t h e i r a f f e c t ( s e e L i n e p r o p e r t i e s a n d L i n e s t y l e s b e l o w ) . C h a n g i n g c o l o r s a n d l i n e w i d t h s D o c u m e n t a t i o n ● C o n t r o l l i n g l i n e p r o p e r t i e s ● L i n e A P I A s a f i r s t s t e p , w e w a n t t o h a v e t h e c o s i n e i n b l u e a n d t h e s i n e i n r e d a n d a
s l i g h t l y t h i c k e r l i n e f o r b o t h o f t h e m . W e ' l l a l s o s l i g h t l y a l t e r t h e f i g u r e
s i z e t o m a k e i t m o r e h o r i z o n t a l .
...
plt.figure(figsize=(10,6), dpi=80)
plt.plot(X, C, color="blue", linewidth=2.5, linestyle="-")
plt.plot(X, S, color="red", linewidth=2.5, linestyle="-")
...
S e t t i n g l i m i t s D o c u m e n t a t i o n ● x l i m ( ) c o m m a n d ● y l i m ( ) c o m m a n d C u r r e n t l i m i t s o f t h e f i g u r e a r e a b i t t o o t i g h t a n d w e w a n t t o m a k e s o m e s p a c e
i n o r d e r t o c l e a r l y s e e a l l d a t a p o i n t s .
...
plt.xlim(X.min()*1.1, X.max()*1.1)
plt.ylim(C.min()*1.1, C.max()*1.1)
...
S e t t i n g t i c k s D o c u m e n t a t i o n ● x t i c k s ( ) c o m m a n d ● y t i c k s ( ) c o m m a n d ● T i c k c o n t a i n e r ● T i c k l o c a t i n g a n d f o r m a t t i n g C u r r e n t t i c k s a r e n o t i d e a l b e c a u s e t h e y d o n o t s h o w t h e i n t e r e s t i n g v a l u e s
( + / - π , + / - π / 2 ) f o r s i n e a n d c o s i n e . W e ' l l c h a n g e t h e m s u c h t h a t t h e y s h o w o n l y
t h e s e v a l u e s .
...
plt.xticks( [-np.pi, -np.pi/2, 0, np.pi/2, np.pi])
plt.yticks([-1, 0, +1])
...
S e t t i n g t i c k l a b e l s D o c u m e n t a t i o n ● W o r k i n g w i t h t e x t ● x t i c k s ( ) c o m m a n d ● y t i c k s ( ) c o m m a n d ● s e t _ x t i c k l a b e l s ( ) ● s e t _ y t i c k l a b e l s ( ) T i c k s a r e n o w p r o p e r l y p l a c e d b u t t h e i r l a b e l i s n o t v e r y e x p l i c i t . W e c o u l d
g u e s s t h a t 3 . 1 4 2 i s π b u t i t w o u l d b e b e t t e r t o m a k e i t e x p l i c i t . W h e n w e s e t
t i c k v a l u e s , w e c a n a l s o p r o v i d e a c o r r e s p o n d i n g l a b e l i n t h e s e c o n d a r g u m e n t
l i s t . N o t e t h a t w e ' l l u s e l a t e x t o a l l o w f o r n i c e r e n d e r i n g o f t h e l a b e l .
...
plt.xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi],
[r'$-\pi$', r'$-\pi/2$', r'$0$', r'$+\pi/2$', r'$+\pi$'])
plt.yticks([-1, 0, +1],
[r'$-1$', r'$0$', r'$+1$'])
...
M o v i n g s p i n e s D o c u m e n t a t i o n ● S p i n e s ● A x i s c o n t a i n e r ● T r a n s f o r m a t i o n s t u t o r i a l S p i n e s a r e t h e l i n e s c o n n e c t i n g t h e a x i s t i c k m a r k s a n d n o t i n g t h e b o u n d a r i e s
o f t h e d a t a a r e a . T h e y c a n b e p l a c e d a t a r b i t r a r y p o s i t i o n s a n d u n t i l n o w , t h e y
w e r e o n t h e b o r d e r o f t h e a x i s . W e ' l l c h a n g e t h a t s i n c e w e w a n t t o h a v e t h e m i n
t h e m i d d l e . S i n c e t h e r e a r e f o u r o f t h e m ( t o p / b o t t o m / l e f t / r i g h t ) , w e ' l l d i s c a r d
t h e t o p a n d r i g h t b y s e t t i n g t h e i r c o l o r t o n o n e a n d w e ' l l m o v e t h e b o t t o m a n d
l e f t o n e s t o c o o r d i n a t e 0 i n d a t a s p a c e c o o r d i n a t e s .
...
ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.spines['bottom'].set_position(('data',0))
ax.yaxis.set_ticks_position('left')
ax.spines['left'].set_position(('data',0))
...
A d d i n g a l e g e n d D o c u m e n t a t i o n ● L e g e n d g u i d e ● l e g e n d ( ) c o m m a n d ● L e g e n d A P I L e t ' s a d d a l e g e n d i n t h e u p p e r l e f t c o r n e r . T h i s o n l y r e q u i r e s a d d i n g t h e
k e y w o r d a r g u m e n t l a b e l ( t h a t w i l l b e u s e d i n t h e l e g e n d b o x ) t o t h e p l o t
c o m m a n d s .
...
plt.plot(X, C, color="blue", linewidth=2.5, linestyle="-", label="cosine")
plt.plot(X, S, color="red", linewidth=2.5, linestyle="-", label="sine")
plt.legend(loc='upper left', frameon=False)
...
A n n o t a t e s o m e p o i n t s D o c u m e n t a t i o n ● A n n o t a t i n g a x i s ● a n n o t a t e ( ) c o m m a n d L e t ' s a n n o t a t e s o m e i n t e r e s t i n g p o i n t s u s i n g t h e a n n o t a t e c o m m a n d . W e c h o o s e t h e
2 π / 3 v a l u e a n d w e w a n t t o a n n o t a t e b o t h t h e s i n e a n d t h e c o s i n e . W e ' l l f i r s t
d r a w a m a r k e r o n t h e c u r v e a s w e l l a s a s t r a i g h t d o t t e d l i n e . T h e n , w e ' l l u s e
t h e a n n o t a t e c o m m a n d t o d i s p l a y s o m e t e x t w i t h a n a r r o w .
...
t = 2*np.pi/3
plt.plot([t,t],[0,np.cos(t )], color ='blue', linewidth=1.5, linestyle="--")
plt.scatter([t,],[np.cos(t ),], 50, color ='blue')
plt.annotate(r'$\sin(\frac{2\pi}{3})=\frac{\sqrt{3}}{2}$',
xy=(t, np.sin(t )), xycoords='data',
xytext=(+10, +30), textcoords='offset points', fontsize=16,
arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=.2"))
plt.plot([t,t],[0,np.sin(t )], color ='red', linewidth=1.5, linestyle="--")
plt.scatter([t,],[np.sin(t ),], 50, color ='red')
plt.annotate(r'$\cos(\frac{2\pi}{3})=-\frac{1}{2}$',
xy=(t, np.cos(t )), xycoords='data',
xytext=(-90, -50), textcoords='offset points', fontsize=16,
arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=.2"))
...
D e v i l i s i n t h e d e t a i l s D o c u m e n t a t i o n ● A r t i s t s ● B B o x T h e t i c k l a b e l s a r e n o w h a r d l y v i s i b l e b e c a u s e o f t h e b l u e a n d r e d l i n e s . W e c a n
m a k e t h e m b i g g e r a n d w e c a n a l s o a d j u s t t h e i r p r o p e r t i e s s u c h t h a t t h e y ' l l b e
r e n d e r e d o n a s e m i - t r a n s p a r e n t w h i t e b a c k g r o u n d . T h i s w i l l a l l o w u s t o s e e b o t h
t h e d a t a a n d t h e l a b e l s .
...
for label in ax.get_xticklabels() + ax.get_yticklabels():
label.set_fontsize(16 )
label.set_bbox(dict(facecolor='white', edgecolor='None', alpha=0.65 ))
...
S o f a r w e h a v e u s e d i m p l i c i t f i g u r e a n d a x e s c r e a t i o n . T h i s i s h a n d y f o r f a s t
p l o t s . W e c a n h a v e m o r e c o n t r o l o v e r t h e d i s p l a y u s i n g f i g u r e , s u b p l o t , a n d
a x e s e x p l i c i t l y . A f i g u r e i n m a t p l o t l i b m e a n s t h e w h o l e w i n d o w i n t h e u s e r
i n t e r f a c e . W i t h i n t h i s f i g u r e t h e r e c a n b e s u b p l o t s . W h i l e s u b p l o t p o s i t i o n s
t h e p l o t s i n a r e g u l a r g r i d , a x e s a l l o w s f r e e p l a c e m e n t w i t h i n t h e f i g u r e . B o t h
c a n b e u s e f u l d e p e n d i n g o n y o u r i n t e n t i o n . W e ' v e a l r e a d y w o r k e d w i t h f i g u r e s
a n d s u b p l o t s w i t h o u t e x p l i c i t l y c a l l i n g t h e m . W h e n w e c a l l p l o t , m a t p l o t l i b
c a l l s g c a ( ) t o g e t t h e c u r r e n t a x e s a n d g c a i n t u r n c a l l s g c f ( ) t o g e t t h e
c u r r e n t f i g u r e . I f t h e r e i s n o n e i t c a l l s f i g u r e ( ) t o m a k e o n e , s t r i c t l y
s p e a k i n g , t o m a k e a s u b p l o t ( 1 1 1 ) . L e t ' s l o o k a t t h e d e t a i l s . F i g u r e s A f i g u r e i s t h e w i n d o w s i n t h e G U I t h a t h a s " F i g u r e # " a s t i t l e . F i g u r e s
a r e n u m b e r e d s t a r t i n g f r o m 1 a s o p p o s e d t o t h e n o r m a l P y t h o n w a y s t a r t i n g
f r o m 0 . T h i s i s c l e a r l y M A T L A B - s t y l e . T h e r e a r e s e v e r a l p a r a m e t e r s t h a t
d e t e r m i n e w h a t t h e f i g u r e l o o k s l i k e :
Argument
Default
Description
num
1 number of figure
figsize
figure.figsize
figure size in in inches (width, height)
dpi
figure.dpi
resolution in dots per inch
facecolor
figure.facecolor
color of the drawing background
edgecolor
figure.edgecolor
color of edge around the drawing background
frameon
True
draw figure frame or not
T h e d e f a u l t s c a n b e s p e c i f i e d i n t h e r e s o u r c e f i l e a n d w i l l b e u s e d m o s t o f t h e
t i m e . O n l y t h e n u m b e r o f t h e f i g u r e i s f r e q u e n t l y c h a n g e d . W h e n y o u w o r k w i t h t h e G U I y o u c a n c l o s e a f i g u r e b y c l i c k i n g o n t h e x i n t h e
u p p e r r i g h t c o r n e r . Y o u c a n a l s o c l o s e a f i g u r e p r o g r a m m a t i c a l l y b y c a l l i n g
c l o s e . D e p e n d i n g o n t h e a r g u m e n t i t c l o s e s ( 1 ) t h e c u r r e n t f i g u r e ( n o
a r g u m e n t ) , ( 2 ) a s p e c i f i c f i g u r e ( f i g u r e n u m b e r o r f i g u r e i n s t a n c e a s
a r g u m e n t ) , o r ( 3 ) a l l f i g u r e s ( a l l a s a r g u m e n t ) . A s w i t h o t h e r o b j e c t s , y o u c a n s e t f i g u r e p r o p e r t i e s w i t h t h e s e t _ s o m e t h i n g m e t h o d s . S u b p l o t s W i t h s u b p l o t y o u c a n a r r a n g e p l o t s i n a r e g u l a r g r i d . Y o u n e e d t o s p e c i f y t h e
n u m b e r o f r o w s a n d c o l u m n s a n d t h e n u m b e r o f t h e p l o t . N o t e t h a t t h e g r i d s p e c c o m m a n d i s a m o r e
p o w e r f u l a l t e r n a t i v e . A x e s A x e s a r e v e r y s i m i l a r t o s u b p l o t s b u t a l l o w p l a c e m e n t o f p l o t s a t a n y l o c a t i o n
i n t h e f i g u r e . S o i f w e w a n t t o p u t a s m a l l e r p l o t i n s i d e a b i g g e r o n e w e d o
s o w i t h a x e s . T i c k s W e l l f o r m a t t e d t i c k s a r e a n i m p o r t a n t p a r t o f p u b l i s h i n g - r e a d y
f i g u r e s . M a t p l o t l i b p r o v i d e s a t o t a l l y c o n f i g u r a b l e s y s t e m f o r t i c k s . T h e r e a r e
t i c k l o c a t o r s t o s p e c i f y w h e r e t i c k s s h o u l d a p p e a r a n d t i c k f o r m a t t e r s t o g i v e
t i c k s t h e a p p e a r a n c e y o u w a n t . M a j o r a n d m i n o r t i c k s c a n b e l o c a t e d a n d
f o r m a t t e d i n d e p e n d e n t l y f r o m e a c h o t h e r . B y d e f a u l t m i n o r t i c k s a r e n o t s h o w n ,
i . e . t h e r e i s o n l y a n e m p t y l i s t f o r t h e m b e c a u s e i t i s a s N u l l L o c a t o r ( s e e
b e l o w ) . T i c k L o c a t o r s T h e r e a r e s e v e r a l l o c a t o r s f o r d i f f e r e n t k i n d o f r e q u i r e m e n t s :
Class
Description
NullLocator
No ticks.
IndexLocator
Place a tick on every multiple of some base number of points plotted.
FixedLocator
Tick locations are fixed.
LinearLocator
Determine the tick locations.
MultipleLocator
Set a tick on every integer that is multiple of some base.
AutoLocator
Select no more than n intervals at nice locations.
LogLocator
Determine the tick locations for log axes.
A l l o f t h e s e l o c a t o r s d e r i v e f r o m t h e b a s e c l a s s m a t p l o t l i b . t i c k e r . L o c a t o r .
Y o u c a n m a k e y o u r o w n l o c a t o r d e r i v i n g f r o m i t . H a n d l i n g d a t e s a s t i c k s c a n b e
e s p e c i a l l y t r i c k y . T h e r e f o r e , m a t p l o t l i b p r o v i d e s s p e c i a l l o c a t o r s i n
m a t p l o t l i b . d a t e s . F o r q u i t e a l o n g t i m e , a n i m a t i o n i n m a t p l o t l i b w a s n o t a n e a s y t a s k a n d w a s
d o n e m a i n l y t h r o u g h c l e v e r h a c k s . H o w e v e r , t h i n g s h a v e s t a r t e d t o c h a n g e s i n c e
v e r s i o n 1 . 1 a n d t h e i n t r o d u c t i o n o f t o o l s f o r c r e a t i n g a n i m a t i o n v e r y
i n t u i t i v e l y , w i t h t h e p o s s i b i l i t y t o s a v e t h e m i n a l l k i n d o f f o r m a t s ( b u t d o n ' t
e x p e c t t o b e a b l e t o r u n v e r y c o m p l e x a n i m a t i o n s a t 6 0 f p s t h o u g h ) . D o c u m e n t a t i o n ● S e e A n i m a t i o n T h e m o s t e a s y w a y t o m a k e a n a n i m a t i o n i n m a t p l o t l i b i s t o d e c l a r e a
F u n c A n i m a t i o n o b j e c t t h a t s p e c i f i e s t o m a t p l o t l i b w h a t i s t h e f i g u r e t o
u p d a t e , w h a t i s t h e u p d a t e f u n c t i o n a n d w h a t i s t h e d e l a y b e t w e e n f r a m e s . D r i p d r o p A v e r y s i m p l e r a i n e f f e c t c a n b e o b t a i n e d b y h a v i n g s m a l l g r o w i n g r i n g s
r a n d o m l y p o s i t i o n e d o v e r a f i g u r e . O f c o u r s e , t h e y w o n ' t g r o w f o r e v e r s i n c e t h e
w a v e i s s u p p o s e d t o d a m p w i t h t i m e . T o s i m u l a t e t h a t , w e c a n u s e a m o r e a n d
m o r e t r a n s p a r e n t c o l o r a s t h e r i n g i s g r o w i n g , u p t o t h e p o i n t w h e r e i t i s n o
m o r e v i s i b l e . A t t h i s p o i n t , w e r e m o v e t h e r i n g a n d c r e a t e a n e w o n e . F i r s t s t e p i s t o c r e a t e a b l a n k f i g u r e : # New figure with white background
fig = plt .figure (figsize = (6 6 facecolor = 'white' )
# New axis over the whole figure, no frame and a 1:1 aspect ratio
ax = fig .add_axes ([0 ,0 ,1 1 frameon = False , aspect = 1 N e x t , w e n e e d t o c r e a t e s e v e r a l r i n g s . F o r t h i s , w e c a n u s e t h e s c a t t e r p l o t
o b j e c t t h a t i s g e n e r a l l y u s e d t o v i s u a l i z e p o i n t s c l o u d , b u t w e c a n a l s o u s e i t
t o d r a w r i n g s b y s p e c i f y i n g w e d o n ' t h a v e a f a c e c o l o r . W e a l s o h a v e t o t a k e
c a r e o f i n i t i a l s i z e a n d c o l o r f o r e a c h r i n g s u c h t h a t w e h a v e a l l s i z e s b e t w e e n
a m i n i m u m a n d a m a x i m u m s i z e . I n a d d i t i o n , w e n e e d t o m a k e s u r e t h e l a r g e s t r i n g
i s a l m o s t t r a n s p a r e n t . # Number of ring
n = 50 size_min = 50 size_max = 50 * 50 # Ring position
P = np random .uniform (0 ,1 n 2 # Ring colors
C = np ones ((n 4 * (0 ,0 ,0 ,1 # Alpha color channel goes from 0 (transparent) to 1 (opaque)
C 3 = np linspace (0 ,1 n # Ring sizes
S = np linspace (size_min , size_max , n # Scatter plot
scat = ax scatter (P 0 ], P 1 s = S lw = 0.5 ,
edgecolors = C facecolors = 'None' )
# Ensure limits are [0,1] and remove ticks
ax set_xlim (0 ,1 ax set_xticks ([])
ax set_ylim (0 ,1 ax set_yticks ([])N o w , w e n e e d t o w r i t e t h e u p d a t e f u n c t i o n f o r o u r a n i m a t i o n . W e k n o w t h a t a t
e a c h t i m e s t e p e a c h r i n g s h o u l d g r o w a n d b e c o m e m o r e t r a n s p a r e n t w h i l e t h e
l a r g e s t r i n g s h o u l d b e t o t a l l y t r a n s p a r e n t a n d t h u s r e m o v e d . O f c o u r s e , w e w o n ' t
a c t u a l l y r e m o v e t h e l a r g e s t r i n g b u t r e - u s e i t t o s e t a n e w r i n g a t a n e w r a n d o m
p o s i t i o n , w i t h n o m i n a l s i z e a n d c o l o r . H e n c e , w e k e e p t h e n u m b e r o f r i n g s
c o n s t a n t . def update (frame ):
global P C S # Every ring is made more transparent
C 3 = np maximum (0 , C 3 - 1.0 / n # Each ring is made larger
S += (size_max - size_min ) / n # Reset ring specific ring (relative to frame number)
i = frame % 50 P i = np random .uniform (0 ,1 2 S i = size_min
C i 3 = 1 # Update scatter object
scat .set_edgecolors (C scat .set_sizes (S scat .set_offsets (P # Return the modified object
return scat ,L a s t s t e p i s t o t e l l m a t p l o t l i b t o u s e t h i s f u n c t i o n a s a n u p d a t e f u n c t i o n f o r
t h e a n i m a t i o n a n d d i s p l a y t h e r e s u l t o r s a v e i t a s a m o v i e : animation = FuncAnimation (fig , update , interval = 10 blit = True , frames = 200 )
# animation.save('rain.gif', writer='imagemagick', fps=30, dpi=40)
plt .show ()E a r t h q u a k e s W e ' l l n o w u s e t h e r a i n a n i m a t i o n t o v i s u a l i z e e a r t h q u a k e s o n t h e p l a n e t f r o m
t h e l a s t 3 0 d a y s . T h e U S G S E a r t h q u a k e H a z a r d s P r o g r a m i s p a r t o f t h e N a t i o n a l
E a r t h q u a k e H a z a r d s R e d u c t i o n P r o g r a m ( N E H R P ) a n d p r o v i d e s s e v e r a l d a t a o n t h e i r
w e b s i t e . T h o s e d a t a a r e s o r t e d a c c o r d i n g t o
e a r t h q u a k e s m a g n i t u d e , r a n g i n g f r o m s i g n i f i c a n t o n l y d o w n t o a l l e a r t h q u a k e s ,
m a j o r o r m i n o r . Y o u w o u l d b e s u r p r i s e d b y t h e n u m b e r o f m i n o r e a r t h q u a k e s
h a p p e n i n g e v e r y h o u r o n t h e p l a n e t . S i n c e t h i s w o u l d r e p r e s e n t t o o m u c h d a t a
f o r u s , w e ' l l s t i c k t o e a r t h q u a k e s w i t h m a g n i t u d e > 4 . 5 . A t t h e t i m e o f w r i t i n g ,
t h i s a l r e a d y r e p r e s e n t m o r e t h a n 3 0 0 e a r t h q u a k e s i n t h e l a s t 3 0 d a y s . F i r s t s t e p i s t o r e a d a n d c o n v e r t d a t a . W e ' l l u s e t h e u r l l i b l i b r a r y t h a t
a l l o w s u s t o o p e n a n d r e a d r e m o t e d a t a . D a t a o n t h e w e b s i t e u s e t h e C S V f o r m a t
w h o s e c o n t e n t i s g i v e n b y t h e f i r s t l i n e :
time,latitude,longitude,depth,mag,magType,nst,gap,dmin,rms,net,id,updated,place,type
2015-08-17T13:49:17.320Z,37.8365,-122.2321667,4.82,4.01,mw,...
2015-08-15T07:47:06.640Z,-10.9045,163.8766,6.35,6.6,mwp,...
W e a r e o n l y i n t e r e s t e d i n l a t i t u d e , l o n g i t u d e a n d m a g n i t u d e a n d w e w o n ' t p a r s e
t i m e o f e v e n t ( o k , t h a t ' s b a d , f e e l f r e e t o s e n d m e a P R ) . import urllib
from mpl_toolkits .basemap import Basemap
# -> http://earthquake.usgs.gov/earthquakes/feed/v1.0/csv.php
feed = "http://earthquake.usgs.gov/earthquakes/feed/v1.0/summary/"
# Significant earthquakes in the last 30 days
# url = urllib.request.urlopen(feed + "significant_month.csv")
# Magnitude > 4.5
url = urllib .request .urlopen (feed + "4.5_month.csv" )
# Magnitude > 2.5
# url = urllib.request.urlopen(feed + "2.5_month.csv")
# Magnitude > 1.0
# url = urllib.request.urlopen(feed + "1.0_month.csv")
# Reading and storage of data
data = url .read ()
data = data .split (b'\n ' )[+ 1 - 1 E = np zeros (len (data ), dtype = [('position' , float , 2 'magnitude' , float , 1 for i in range (len (data )):
row = data [i split (',' )
E 'position' ][i = float (row [2 float (row [1 E 'magnitude' ][i = float (row [4 N o w , w e n e e d t o d r a w t h e e a r t h o n a f i g u r e t o s h o w p r e c i s e l y w h e r e t h e e a r t h q u a k e
c e n t e r i s a n d t o t r a n s l a t e l a t i t u d e / l o n g i t u d e i n s o m e c o o r d i n a t e s m a t p l o t l i b
c a n h a n d l e . F o r t u n a t e l y , t h e r e i s t h e b a s e m a p p r o j e c t ( t h a t t e n d s t o b e r e p l a c e d b y t h e
m o r e c o m p l e t e c a r t o p y ) t h a t i s r e a l l y
s i m p l e t o i n s t a l l a n d t o u s e . F i r s t s t e p i s t o d e f i n e a p r o j e c t i o n t o d r a w t h e
e a r t h o n t o a s c r e e n ( t h e r e e x i s t s m a n y d i f f e r e n t p r o j e c t i o n s ) a n d w e ' l l s t i c k
t o t h e m i l l p r o j e c t i o n w h i c h i s r a t h e r s t a n d a r d f o r n o n - s p e c i a l i s t l i k e m e . fig = plt .figure (figsize = (14 10 ax = plt .subplot (1 1 1 earth = Basemap (projection = 'mill' )N e x t , w e r e q u e s t t o d r a w c o a s t l i n e a n d f i l l c o n t i n e n t s : earth .drawcoastlines (color = '0.50' , linewidth = 0.25 )
earth .fillcontinents (color = '0.95' )T h e e a r t h o b j e c t w i l l a l s o b e u s e d t o t r a n s l a t e c o o r d i n a t e s q u i t e
a u t o m a t i c a l l y . W e a r e a l m o s t f i n i s h e d . L a s t s t e p i s t o a d a p t t h e r a i n c o d e a n d
p u t s o m e e y e c a n d y : P = np zeros (50 dtype = [('position' , float , 2 'size' , float , 1 'growth' , float , 1 'color' , float , 4 scat = ax scatter (P 'position' ][:,0 ], P 'position' ][:,1 P 'size' ], lw = 0.5 ,
edgecolors = P 'color' ], facecolors = 'None' , zorder = 10 def update (frame ):
current = frame % len (E i = frame % len (P P 'color' ][:,3 = np maximum (0 , P 'color' ][:,3 - 1.0 / len (P P 'size' ] += P 'growth' ]
magnitude = E 'magnitude' ][current ]
P 'position' ][i = earth (* E 'position' ][current ])
P 'size' ][i = 5 P 'growth' ][i = np exp (magnitude ) * 0.1
if magnitude < 6 P 'color' ][i = 0 ,0 ,1 1 else :
P 'color' ][i = 1 0 ,0 ,1 scat .set_edgecolors (P 'color' ])
scat .set_facecolors (P 'color' ]* (1 1 1 0.25 ))
scat .set_sizes (P 'size' ])
scat .set_offsets (P 'position' ])
return scat ,
animation = FuncAnimation (fig , update , interval = 10 plt .show ()I f e v e r y t h i n g w e n t w e l l , y o u s h o u l d o b t a i n s o m e t h i n g l i k e t h i s ( w i t h a n i m a t i o n ) : R e g u l a r P l o t s H i n t s Y o u n e e d t o u s e t h e f i l l _ b e t w e e n c o m m a n d . S t a r t i n g f r o m t h e c o d e b e l o w , t r y t o r e p r o d u c e t h e g r a p h i c o n t h e r i g h t t a k i n g
c a r e o f f i l l e d a r e a s .
import numpy as np
import matplotlib.pyplot as plt
n = 256
X = np.linspace(-np.pi,np.pi,n,endpoint=True)
Y = np.sin(2*X)
plt.plot (X, Y+1, color='blue', alpha=1.00)
plt.plot (X, Y-1, color='blue', alpha=1.00)
plt.show()
C l i c k o n f i g u r e f o r s o l u t i o n . S c a t t e r P l o t s H i n t s C o l o r i s g i v e n b y a n g l e o f ( X , Y ) . S t a r t i n g f r o m t h e c o d e b e l o w , t r y t o r e p r o d u c e t h e g r a p h i c o n t h e r i g h t t a k i n g
c a r e o f m a r k e r s i z e , c o l o r a n d t r a n s p a r e n c y .
import numpy as np
import matplotlib.pyplot as plt
n = 1024
X = np.random.normal(0,1,n)
Y = np.random.normal(0,1,n)
plt.scatter(X,Y)
plt.show()
C l i c k o n f i g u r e f o r s o l u t i o n . B a r P l o t s H i n t s Y o u n e e d t o t a k e c a r e o f t e x t a l i g n m e n t . S t a r t i n g f r o m t h e c o d e b e l o w , t r y t o r e p r o d u c e t h e g r a p h i c o n t h e r i g h t b y
a d d i n g l a b e l s f o r r e d b a r s .
import numpy as np
import matplotlib.pyplot as plt
n = 12
X = np.arange(n )
Y1 = (1-X/float(n )) * np.random.uniform(0.5,1.0,n)
Y2 = (1-X/float(n )) * np.random.uniform(0.5,1.0,n)
plt.bar(X, +Y1, facecolor='#9999ff', edgecolor='white')
plt.bar(X, -Y2, facecolor='#ff9999', edgecolor='white')
for x,y in zip(X,Y1):
plt.text(x+0.4, y+0.05, '%.2f' % y, ha='center', va= 'bottom')
plt.ylim(-1.25,+1.25)
plt.show()
C l i c k o n f i g u r e f o r s o l u t i o n . C o n t o u r P l o t s H i n t s Y o u n e e d t o u s e t h e c l a b e l c o m m a n d . S t a r t i n g f r o m t h e c o d e b e l o w , t r y t o r e p r o d u c e t h e g r a p h i c o n t h e r i g h t t a k i n g
c a r e o f t h e c o l o r m a p ( s e e C o l o r m a p s b e l o w ) .
import numpy as np
import matplotlib.pyplot as plt
def f(x,y): return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2)
n = 256
x = np.linspace(-3,3,n)
y = np.linspace(-3,3,n)
X,Y = np.meshgrid(x,y)
plt.contourf(X, Y, f(X,Y), 8, alpha=.75, cmap='jet')
C = plt.contour(X, Y, f(X,Y), 8, colors='black', linewidth=.5)
plt.show()
C l i c k o n f i g u r e f o r s o l u t i o n . I m s h o w H i n t s Y o u n e e d t o t a k e c a r e o f t h e o r i g i n o f t h e i m a g e i n t h e i m s h o w c o m m a n d a n d
u s e a c o l o r b a r . S t a r t i n g f r o m t h e c o d e b e l o w , t r y t o r e p r o d u c e t h e g r a p h i c o n t h e r i g h t t a k i n g
c a r e o f c o l o r m a p , i m a g e i n t e r p o l a t i o n a n d o r i g i n .
import numpy as np
import matplotlib.pyplot as plt
def f(x,y): return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2)
n = 10
x = np.linspace(-3,3,4*n)
y = np.linspace(-3,3,3*n)
X,Y = np.meshgrid(x,y)
plt.imshow(f(X,Y))
plt.show()
C l i c k o n f i g u r e f o r s o l u t i o n . P i e C h a r t s H i n t s Y o u n e e d t o m o d i f y Z . S t a r t i n g f r o m t h e c o d e b e l o w , t r y t o r e p r o d u c e t h e g r a p h i c o n t h e r i g h t t a k i n g
c a r e o f c o l o r s a n d s l i c e s s i z e .
import numpy as np
import matplotlib.pyplot as plt
n = 20
Z = np.random.uniform(0,1,n)
plt.pie(Z )
plt.show()
C l i c k o n f i g u r e f o r s o l u t i o n . Q u i v e r P l o t s H i n t s Y o u n e e d t o d r a w a r r o w s t w i c e . S t a r t i n g f r o m t h e c o d e a b o v e , t r y t o r e p r o d u c e t h e g r a p h i c o n t h e r i g h t t a k i n g
c a r e o f c o l o r s a n d o r i e n t a t i o n s .
import numpy as np
import matplotlib.pyplot as plt
n = 8
X,Y = np.mgrid[0:n,0:n]
plt.quiver(X,Y)
plt.show()
C l i c k o n f i g u r e f o r s o l u t i o n . G r i d s S t a r t i n g f r o m t h e c o d e b e l o w , t r y t o r e p r o d u c e t h e g r a p h i c o n t h e r i g h t t a k i n g
c a r e o f l i n e s t y l e s .
import numpy as np
import matplotlib.pyplot as plt
axes = gca()
axes.set_xlim(0,4)
axes.set_ylim(0,3)
axes.set_xticklabels([])
axes.set_yticklabels([])
plt.show()
C l i c k o n f i g u r e f o r s o l u t i o n . M u l t i P l o t s H i n t s Y o u c a n u s e s e v e r a l s u b p l o t s w i t h d i f f e r e n t p a r t i t i o n . S t a r t i n g f r o m t h e c o d e b e l o w , t r y t o r e p r o d u c e t h e g r a p h i c o n t h e r i g h t .
import numpy as np
import matplotlib.pyplot as plt
plt.subplot(2,2,1)
plt.subplot(2,2,3)
plt.subplot(2,2,4)
plt.show()
C l i c k o n f i g u r e f o r s o l u t i o n . P o l a r A x i s H i n t s Y o u o n l y n e e d t o m o d i f y t h e a x e s l i n e . S t a r t i n g f r o m t h e c o d e b e l o w , t r y t o r e p r o d u c e t h e g r a p h i c o n t h e r i g h t .
import numpy as np
import matplotlib.pyplot as plt
plt.axes([0,0,1,1])
N = 20
theta = np.arange(0.0, 2*np.pi, 2*np.pi/N)
radii = 10*np.random.rand(N )
width = np.pi/4*np.random.rand(N )
bars = plt.bar(theta, radii, width=width, bottom=0.0)
for r,bar in zip(radii, bars):
bar.set_facecolor( cm.jet(r/10.))
bar.set_alpha(0.5)
plt.show()
C l i c k o n f i g u r e f o r s o l u t i o n . 3 D P l o t s H i n t s Y o u n e e d t o u s e c o n t o u r f . S t a r t i n g f r o m t h e c o d e b e l o w , t r y t o r e p r o d u c e t h e g r a p h i c o n t h e r i g h t .
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = Axes3D(fig)
X = np.arange(-4, 4, 0.25)
Y = np.arange(-4, 4, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R )
ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap='hot')
plt.show()
C l i c k o n f i g u r e f o r s o l u t i o n . T e x t H i n t s H a v e a l o o k a t t h e m a t p l o t l i b l o g o . T r y t o d o t h e s a m e f r o m s c r a t c h ! C l i c k o n f i g u r e f o r s o l u t i o n . M a t p l o t l i b b e n e f i t s f r o m e x t e n s i v e d o c u m e n t a t i o n a s w e l l a s a l a r g e
c o m m u n i t y o f u s e r s a n d d e v e l o p p e r s . H e r e a r e s o m e l i n k s o f i n t e r e s t : T u t o r i a l s ● P y p l o t t u t o r i a l ● I n t r o d u c t i o n ● C o n t r o l l i n g l i n e p r o p e r t i e s ● W o r k i n g w i t h m u l t i p l e f i g u r e s a n d a x e s ● W o r k i n g w i t h t e x t ● I m a g e t u t o r i a l ● S t a r t u p c o m m a n d s ● I m p o r t i n g i m a g e d a t a i n t o N u m p y a r r a y s ● P l o t t i n g n u m p y a r r a y s a s i m a g e s ● T e x t t u t o r i a l ● T e x t i n t r o d u c t i o n ● B a s i c t e x t c o m m a n d s ● T e x t p r o p e r t i e s a n d l a y o u t ● W r i t i n g m a t h e m a t i c a l e x p r e s s i o n s ● T e x t r e n d e r i n g W i t h L a T e X ● A n n o t a t i n g t e x t ● A r t i s t t u t o r i a l ● I n t r o d u c t i o n ● C u s t o m i z i n g y o u r o b j e c t s ● O b j e c t c o n t a i n e r s ● F i g u r e c o n t a i n e r ● A x e s c o n t a i n e r ● A x i s c o n t a i n e r s ● T i c k c o n t a i n e r s ● P a t h t u t o r i a l ● I n t r o d u c t i o n ● B é z i e r e x a m p l e ● C o m p o u n d p a t h s ● T r a n s f o r m s t u t o r i a l ● I n t r o d u c t i o n ● D a t a c o o r d i n a t e s ● A x e s c o o r d i n a t e s ● B l e n d e d t r a n s f o r m a t i o n s ● U s i n g o f f s e t t r a n s f o r m s t o c r e a t e a s h a d o w e f f e c t ● T h e t r a n s f o r m a t i o n p i p e l i n e M a t p l o t l i b d o c u m e n t a t i o n ● U s e r g u i d e ● F A Q ● I n s t a l l a t i o n ● U s a g e ● H o w - T o ● T r o u b l e s h o o t i n g ● E n v i r o n m e n t V a r i a b l e s ● S c r e e n s h o t s C o d e d o c u m e n t a t i o n T h e c o d e i s f a i r l y w e l l d o c u m e n t e d a n d y o u c a n q u i c k l y a c c e s s a s p e c i f i c
c o m m a n d f r o m w i t h i n a p y t h o n s e s s i o n :
>>> import matplotlib.pyplot as plt
>>> help(plt)
Help on function plot in module matplotlib.pyplot:
plot(*args, **kwargs)
Plot lines and/or markers to the
:class:`~matplotlib.axes.Axes`. *args* is a variable length
argument, allowing for multiple *x*, *y* pairs with an
optional format string. For example, each of the following is
legal::
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+') # ditto, but with red plusses
If *x* and/or *y* is 2-dimensional, then the corresponding columns
will be plotted.
...
G a l l e r i e s T h e m a t p l o t l i b g a l l e r y i s
a l s o i n c r e d i b l y u s e f u l w h e n y o u s e a r c h h o w t o r e n d e r a g i v e n g r a p h i c . E a c h
e x a m p l e c o m e s w i t h i t s s o u r c e . A s m a l l e r g a l l e r y i s a l s o a v a i l a b l e h e r e . M a i l i n g l i s t s F i n a l l y , t h e r e i s a u s e r m a i l i n g l i s t w h e r e y o u c a n
a s k f o r h e l p a n d a d e v e l o p e r s m a i l i n g l i s t t h a t i s m o r e
t e c h n i c a l . H e r e i s a s e t o f t a b l e s t h a t s h o w m a i n p r o p e r t i e s a n d s t y l e s . L i n e p r o p e r t i e s
Property
Description
Appearance
alpha (or a)
alpha transparency on 0-1 scale
antialiased
True or False - use antialised rendering
color (or c)
matplotlib color arg
linestyle (or ls)
see Line properties
linewidth (or lw)
float, the line width in points
solid_capstyle
Cap style for solid lines
solid_joinstyle
Join style for solid lines
dash_capstyle
Cap style for dashes
dash_joinstyle
Join style for dashes
marker
see Markers
markeredgewidth (mew)
line width around the marker symbol
markeredgecolor (mec)
edge color if a marker is used
markerfacecolor (mfc)
face color if a marker is used
markersize (ms )
size of the marker in points
L i n e s t y l e s
Symbol
Description
Appearance
-solid line
--dashed line
-.dash-dot line
:dotted line
.points
,pixels
o circle
^triangle up
v triangle down
<triangle left
>triangle right
s square
+plus
x cross
D diamond
d thin diamond
1 tripod down
2 tripod up
3 tripod left
4 tripod right
h hexagon
H rotated hexagon
p pentagon
|vertical line
_horizontal line
M a r k e r s
Symbol
Description
Appearance
0
tick left
1 tick right
2 tick up
3 tick down
4 caret left
5 caret right
6 caret up
7 caret down
o circle
D diamond
h hexagon 1
H hexagon 2
_horizontal line
1 tripod down
2 tripod up
3 tripod left
4 tripod right
8 octagon
p pentagon
^triangle up
v triangle down
<triangle left
>triangle right
d thin diamond
,pixel
+plus
.point
s square
*star
|vertical line
x cross
r'$\sqrt{2}$'any latex expression
C o l o r m a p s A l l c o l o r m a p s c a n b e r e v e r s e d b y a p p e n d i n g _ r . F o r i n s t a n c e , g r a y _ r i s
t h e r e v e r s e o f g r a y . I f y o u w a n t t o k n o w m o r e a b o u t c o l o r m a p s , s e e D o c u m e n t i n g t h e m a t p l o t l i b
c o l o r m a p s . B a s e
Name
Appearance
autumn
bone
cool
copper
flag
gray
hot
hsv
jet
pink
prism
spectral
spring
summer
winter
G I S T
Name
Appearance
gist_earth
gist_gray
gist_heat
gist_ncar
gist_rainbow
gist_stern
gist_yarg
S e q u e n t i a l
Name
Appearance
BrBG
PiYG
PRGn
PuOr
RdBu
RdGy
RdYlBu
RdYlGn
Spectral
D i v e r g i n g
Name
Appearance
Blues
BuGn
BuPu
GnBu
Greens
Greys
Oranges
OrRd
PuBu
PuBuGn
PuRd
Purples
RdPu
Reds
YlGn
YlGnBu
YlOrBr
YlOrRd
Q u a l i t a t i v e
Name
Appearance
Accent
Dark2
Paired
Pastel1
Pastel2
Set1
Set2
Set3
M i s c e l l a n e o u s
Name
Appearance
afmhot
binary
brg
bwr
coolwarm
CMRmap
cubehelix
gnuplot
gnuplot2
ocean
rainbow
seismic
terrain
A b o u t
M a t p l o t l i b t u t o r i a l f o r b e g i n n e r
T o p i c s
p y t h o n
m a t p l o t l i b
t u t o r i a l
R e s o u r c e s
R e a d m e
V e r s i o n 1 . 0
L a t e s t
A u g 2 1 , 2 0 1 5
N o p a c k a g e s p u b l i s h e d
L a n g u a g e s
●
P y t h o n 8 2 . 8 %
●
C S S 1 5 . 9 %
●
M a k e f i l e 1 . 3 %
● © 2 0 2 0 G i t H u b , I n c . ● T e r m s ● P r i v a c y ● S e c u r i t y ● S t a t u s ● H e l p
● C o n t a c t G i t H u b ● P r i c i n g ● A P I ● T r a i n i n g ● B l o g ● A b o u t
Y o u c a n ’ t p e r f o r m t h a t a c t i o n a t t h i s t i m e .
Y o u s i g n e d i n w i t h a n o t h e r t a b o r w i n d o w . R e l o a d t o r e f r e s h y o u r s e s s i o n . Y o u s i g n e d o u t i n a n o t h e r t a b o r w i n d o w . R e l o a d t o r e f r e s h y o u r s e s s i o n . 
Table of Contents
●Introduction
●Simple plot
●Figures, Subplots, Axes and Ticks
●Animation
●Other Types of Plots
●Beyond this tutorial
●Quick references
Sources are available from
github
All code and material is licensed under a Creative Commons
Attribution-ShareAlike 4.0.
You can test your installation before the tutorial using the check-installation.py script.
See also:
●From Python to Numpy
●100 Numpy exercices
●Ten simple rules for better figures
Matplotlib comes with a set of default settings that allow customizing all
kinds of properties. You can control the defaults of almost every property in
matplotlib: figure size and dpi, line width, color and style, axes, axis and
grid properties, text and font properties and so on. While matplotlib defaults
are rather good in most cases, you may want to modify some properties for
specific cases.
In the script below, we've instantiated (and commented) all the figure settings
that influence the appearance of the plot. The settings have been explicitly
set to their default values, but now you can interactively play with the values
to explore their affect (see Line properties and Line styles below).
As a first step, we want to have the cosine in blue and the sine in red and a
slightly thicker line for both of them. We'll also slightly alter the figure
size to make it more horizontal.
Current limits of the figure are a bit too tight and we want to make some space
in order to clearly see all data points.
Current ticks are not ideal because they do not show the interesting values
(+/-π,+/-π/2) for sine and cosine. We'll change them such that they show only
these values.
Ticks are now properly placed but their label is not very explicit. We could
guess that 3.142 is π but it would be better to make it explicit. When we set
tick values, we can also provide a corresponding label in the second argument
list. Note that we'll use latex to allow for nice rendering of the label.
Spines are the lines connecting the axis tick marks and noting the boundaries
of the data area. They can be placed at arbitrary positions and until now, they
were on the border of the axis. We'll change that since we want to have them in
the middle. Since there are four of them (top/bottom/left/right), we'll discard
the top and right by setting their color to none and we'll move the bottom and
left ones to coordinate 0 in data space coordinates.
Let's add a legend in the upper left corner. This only requires adding the
keyword argument label (that will be used in the legend box) to the plot
commands.
Let's annotate some interesting points using the annotate command. We choose the
2π/3 value and we want to annotate both the sine and the cosine. We'll first
draw a marker on the curve as well as a straight dotted line. Then, we'll use
the annotate command to display some text with an arrow.
The tick labels are now hardly visible because of the blue and red lines. We can
make them bigger and we can also adjust their properties such that they'll be
rendered on a semi-transparent white background. This will allow us to see both
the data and the labels.
Hints
You need to use the fill_between
command.
Starting from the code below, try to reproduce the graphic on the right taking
care of filled areas.
Hints
Color is given by angle of (X,Y).
Starting from the code below, try to reproduce the graphic on the right taking
care of marker size, color and transparency.
Hints
You need to take care of text alignment.
Starting from the code below, try to reproduce the graphic on the right by
adding labels for red bars.
Hints
You need to use the clabel
command.
Starting from the code below, try to reproduce the graphic on the right taking
care of the colormap (see Colormaps below).
Hints
You need to take care of the 
Hints
You need to modify Z.
Starting from the code below, try to reproduce the graphic on the right taking
care of colors and slices size.
Hints
You need to draw arrows twice.
Starting from the code above, try to reproduce the graphic on the right taking
care of colors and orientations.
Starting from the code below, try to reproduce the graphic on the right taking
care of line styles.
Hints
You can use several subplots with different partition.
Starting from the code below, try to reproduce the graphic on the right.
Hints
You only need to modify the 
Hints
You need to use contourf.
Starting from the code below, try to reproduce the graphic on the right.
Hints
Have a look at the matplotlib logo.
Try to do the same from scratch!
Click on figure for solution.
