In [1]:

    

%pylab inline


    

    




Populating the interactive namespace from numpy and matplotlib

In [2]:

    

from beeswarm import *
import numpy as np


    

In [3]:

    

d1 = np.random.normal(size=100)


    

In [4]:

    

beeswarm([d1], method="swarm");


    

In [5]:

    

beeswarm([d1], method="hex");


    

In [6]:

    

beeswarm([d1], method="center");


    

In [7]:

    

beeswarm([d1], method="square");


    

In [8]:

    

beeswarm(d1);


    

In [9]:

    

beeswarm([d1, d1]);


    

In [10]:

    

beeswarm([d1]*4);


    

In [11]:

    

d2 = np.random.uniform(low=-5, high=0, size=100)
beeswarm([d1,d1,d2], positions=[1,2, 5], labels=["test1","test2","test3"], col=["red","green","orange"]);


    

In [12]:

    

beeswarm([d1,d2,d2], xlim=(-2,5), ylim=(-6,6));


    

In [13]:

    

beeswarm([d1,d2,d2], xlim=(-2,5));


    

In [14]:

    

fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_xlim(left=-2, right=6)
ax.set_ylim(bottom=-10, top=10)
bs, ax = beeswarm([d1,d1,d2,d2], positions=[0,3,5,6], ax=ax, col=["red","orange","yellow"]);
ax.set_xlabel("testing x")


    

    
Out[14]:





<matplotlib.text.Text at 0x4bb6ad0>






    

In [15]:

    

bs.head()


    

    
Out[15]:






  

    

      

      
color
      
xnew
      
xorig
      
ynew
      
yorig
    
  
  

    

      
0
      
    red
      
 0.000000
      
 0
      
-3.233790
      
-3.233790
    
    

      
1
      
 orange
      
 0.000000
      
 0
      
-2.594117
      
-2.594117
    
    

      
2
      
 yellow
      
 0.000000
      
 0
      
-2.362106
      
-2.362106
    
    

      
3
      
    red
      
 0.000000
      
 0
      
-1.962170
      
-1.962170
    
    

      
4
      
 orange
      
 0.123496
      
 0
      
-1.955887
      
-1.955887
    
  

5 rows × 5 columns

In [16]:

    

beeswarm([])


    

In [17]:

    

beeswarm([d1], positions=[])


    

    




ERROR: number of positions must match number of groups

In [18]:

    

beeswarm([d1], method="dummy")


    

    




ERROR: Invalid method.

In [19]:

    

beeswarm([d1], col=2)


    

    




ERROR: Invalid argument for col

In [20]:

    

d1 = np.random.normal(size=100)
d2 = np.random.normal(loc=1, size=100)
d3 = np.random.normal(scale=2, size=100)
d4 = np.random.uniform(low=-3, high=3, size=100)

bs, ax = beeswarm([d1,d2,d3,d4], col=["red","orange","yellow"], labels=["N(0,1)", "N(1,1)", "N(0,2)","Unif(-3,3)"])
ax.set_xticklabels(["N(0,1)", "N(1,1)", "N(0,2)","Unif(-3,3)"], size=15);
ax.set_yticklabels(np.arange(-4,7,2), size=15);
plt.savefig("example.png")