Qiita Teams that are logged in
You are not logged in to any team

Community
Service
Qiita JobsQiita ZineQiita Blog
5
Help us understand the problem. What is going on with this article?
@xiangze

# numpyでの人工的データ生成

More than 5 years have passed since last update.

csv形式での出力、scatterplotができます。
c_,r_演算子を使っています。

ツイストされ絡み合った円環(3D)

Lorenzアトラクタ
Rosslerアトラクタ

gendata.py
``````# -*- coding: utf-8 -*-
"""
Created on Wed May 07 21:17:21 2014

@author: xiangze
"""

import csv
import numpy as np
#from matplotlib.pyplot import *
import matplotlib.pyplot as plt

PI=np.pi
PI2=2*PI

def gencircle(rc,rr=0.1,offset=[0,0],num=100,label=0):
c=[]
for i in range(num):
r=rc+np.random.uniform(-rr,rr,1)
th=np.random.uniform(0,PI2,1)
c.append([r*np.sin(th)+offset[0],r*np.cos(th)+offset[1]])
return np.c_[np.array(c).reshape(num,2),np.repeat(label,num)]

def genring(rc,rr=0.1,offset=[0,0,0],num=100,label=0,normaldir='x'):
if(normaldir=='x'):
a=gencircle(rc,rr,[offset[1],offset[2]],num,label)
return np.c_[np.repeat(offset[0],num),a[:,0],a[:,1],a[:,2]]
elif(normaldir=='y'):
a=gencircle(rc,rr,[offset[0],offset[2]],num,label)
return np.c_[a[:,0],np.repeat(offset[1],num),a[:,1],a[:,2]]
else:
a=gencircle(rc,rr,[offset[0],offset[1]],num,label)
return np.c_[a[:,0],a[:,1],np.repeat(offset[2],num),a[:,2]]

def gentwistedring0(rc=[1,0.3],rr=0.1,offset=[0,0,0],num=100,label=0,twistratio=3.0,phase=0):
c=[]
for i in range(num):
r=rc[0]+np.random.uniform(-rr,rr,1)
th=np.random.uniform(0,PI2,1)
c1=[r*np.sin(th)+offset[0],r*np.cos(th)+offset[1],offset[2]]
c2=[rc[1]*np.sin(th*twistratio+phase)*np.sin(th) , rc[1]*np.sin(th*twistratio+phase)*np.cos(th) ,rc[1]*np.cos(th*twistratio+phase)]

c.append([c1[i]+c2[i] for i in range(len(c1))])
return np.c_[np.array(c).reshape(num,3),np.repeat(label,num)]

def gentwistedring(rc=[1,0.3],rr=0.1,offset=[0,0,0],num=100,label=0,normaldir='x',twistratio=5.0,phase=0):
a=gentwistedring0(rc,rr,offset,num,label,twistratio,phase)
if(normaldir=='x'):
return a
elif(normaldir=='y'):
return np.c_[a[:,1],a[:,2],a[:0],a[:3]]
else:
return np.c_[a[:,2],a[:,0],a[:1],a[:3]]

#http://stackoverflow.com/questions/15880367/python-uniform-distribution-of-points-on-4-dimensional-sphere
#Marsaglia's method
def gensphere(rc,rr=0.1,offset=[0,0,0],num=100,label=0,dim=3):
normal_deviates = np.random.normal(size=(dim, num))
r=rc+np.random.uniform(-rr,rr,1)
r = np.sqrt((normal_deviates**2).sum(axis=0))*r
p =normal_deviates/r
return np.c_[np.array(zip(*p)).reshape(num,dim),np.repeat(label,num)]

def gensphere0(rc,rr=0.1,offset=[0,0,0],num=100,label=0):
c=[]
n=int(np.sqrt(num))
for ph in np.random.uniform(-PI,PI,n):
for th in np.random.uniform(0,PI2,n):
r=rc+np.random.uniform(-rr,rr,1)
c.append([r*np.sin(th)*np.sin(ph)+offset[0],r*np.cos(th)*np.sin(ph)+offset[1],r*np.cos(ph)+offset[2]])
return np.c_[np.array(c).reshape(num,3),np.repeat(label,num)]

def gensphere1(rc,rr=0.1,offset=[0,0,0],num=100,label=0):
c=[]
n=int(np.sqrt(num))
for ph in np.random.uniform(-PI,PI,n):
p=0
if(p>=n):
break
else:
m=int(np.abs(np.sin(ph)*n))
if(m!=0):
for th in np.random.uniform(0,PI2,m):
r=rc+np.random.uniform(-rr,rr,1)
c.append((r*np.sin(th)*np.sin(ph)+offset[0],r*np.cos(th)*np.sin(ph)+offset[1],r*np.cos(ph)+offset[2]))
p=p+m
l=len(c)
return np.c_[np.array(c).reshape(l,3),np.repeat(label,l)]

def genlorenz(init=[0,0.1,0],offset=[0,0,0],rr=0.,num=100,p=10,r=28,b=2.66,label=0,dt=0.01):
cc=[]
x=init[0]
y=init[1]
z=init[2]
for t in range(num):
cc.append([x,y,z])
x=x+dt*(-p*x+p*y)      +np.random.uniform(-rr,rr,1)
y=y+dt*(-x*z+r*x-y)    +np.random.uniform(-rr,rr,1)
z=z+dt*( x*y-b*z)      +np.random.uniform(-rr,rr,1)
return np.c_[np.array(cc).reshape(num,3),np.repeat(label,num)]

def genrossler(init=[0,5,0],offset=[0,0,0],num=100,a=0.2,b=0.2,c=5.7,label=0,dt=0.05):
cc=[]
x=init[0]
y=init[1]
z=init[2]
for t in range(num):
cc.append([x,y,z])
x=x+dt*(-y-z)
y=y+dt*( x+a*y)
z=z+dt*( b+z*(x-c))
return np.c_[np.array(cc).reshape(num,3),np.repeat(label,num)]

def cshow2(data):
cc=zip(*data)
plt.scatter(cc[0],cc[1],c=cc[2])
plt.draw()
plt.show()

def cshow3(data):
from mpl_toolkits.mplot3d import Axes3D
fig=plt.figure()
ax = Axes3D(fig)
cc=zip(*data)
ax.scatter(cc[0],cc[1],cc[2],c=cc[3])
plt.draw()
plt.show()

def test(data,dump=False,fname="test.csv"):
if(data.shape[1]==3):
cshow2(data)
else:
cshow3(data)

if(dump):
np.savetxt(fname,data,delimiter=",")

if __name__=="__main__":
num=200
circles=np.vstack([gencircle(1,0.1,num=num,label=0),gencircle(1,0.1,[-2,2],num=num,label=1)])
test(circles)

#circle in circle
cinc=np.r_[gencircle(1,0.1,num=num,label=0),gencircle(2,0.1,num=num,label=1)]
test(cinc)

#XOR-like pattern
xor0=np.r_[gencircle(0.5,num=num/2,offset=[0,0],label=0),gencircle(0.5,offset=[1,1],label=0)]
xor1=np.r_[gencircle(0.5,num=num/2,offset=[0,1],label=1),gencircle(0.5,offset=[1,0],label=1)]
xor=np.r_[xor0,xor1]
test(xor)

#3D ring
rings=np.r_[genring(1,0.1,num=num,offset=[0,0,0],label=0,normaldir='x'),\
genring(1,0.1,num=num,offset=[0,0,1],label=1,normaldir='y')]
test(rings)

num=400
#sphere in sphere
sins=np.r_[gensphere(1,num=num,label=0),gensphere(2,num=num,label=1)]
test(sins)

#twisted rings
test(np.vstack([gentwistedring(num=num,label=0),gentwistedring(num=num,label=1,phase=PI)]))

num=1000
rossler=genrossler(num=num,dt=0.1)
test(rossler)

lorenz=genlorenz(num=num,dt=0.05)
test(lorenz)
``````

5
Help us understand the problem. What is going on with this article?
Why not register and get more from Qiita?
1. We will deliver articles that match you
By following users and tags, you can catch up information on technical fields that you are interested in as a whole
2. you can read useful information later efficiently
By "stocking" the articles you like, you can search right away
https://github.com/xiangze