/
plot_timings.py
148 lines (112 loc) · 3.9 KB
/
plot_timings.py
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from time import time
import numpy as np
from dipy.tracking.distances import local_skeleton_clustering
from dipy.tracking.metrics import downsample,length,winding
from dipy.tracking.vox2track import track_counts
import matplotlib.pyplot as plt
from dipy.io.dpy import Dpy
from dipy.io.pickles import load_pickle,save_pickle
def change_dtype(T,type='f4'):
return [t.astype(type) for t in T]
def plot_timings():
#dir='/home/eg309/Data/LSC_limits/full_1M'
dir='/tmp/full_1M'
fs=['.npy','_2.npy','_3.npy','_4.npy','_5.npy']#,'_6.npy','_7.npy','_8.npy','_9.npy','_10.npy']
T=[]
for f in fs:
fs1=dir+f
T+=change_dtype(list(np.load(fs1)))
#return T
T=T[:100000]
print len(T)
#dists=[4.,6.,8.,10.]
dists=[8.]
#pts=[3,6,12,18]
pts=[12]
#sub=10**5
sub=10**3
res={}
for p in pts:
print p
res[p]={}
for d in dists:
print d
res[p][d]={}
res[p][d]['time']=[]
res[p][d]['len']=[]
step=0
while step <= len(T):
print step
Td=[downsample(t,p) for t in T[0:step+sub]]
t1=time()
C=local_skeleton_clustering(Td,d)
t2=time()
res[p][d]['time'].append(t2-t1)
res[p][d]['len'].append(len(C))
step=step+sub
save_pickle('/tmp/res.pkl',res)
print('Result saved in /tmp/res.pkl')
#return res
save_pickle('/tmp/res.pkl',res)
def show_timings():
res=load_pickle('/home/eg309/Data/LSC_limits/timings_100K_1M.pkl')
#[ 3, 6, 12, 18]
dists=[ 4., 6., 8., 10.]
plt.subplots_adjust(hspace=0.4)
ax1=plt.subplot(221)
plt.title('3 point tracks')
for d in dists:
ax1.plot(res[3][d]['time'][:-2],label=str(d*2.5)+' mm')
ax1.set_ylim((0,6000))
ax1.set_xlim((0,9))
ax1.set_xticklabels(['100K','200K','300K','400K','500K','600K','700K','800K','900K','1M'])
ax1.set_ylabel('Seconds')
ax1.set_xlabel('Number of tracks')
plt.legend()
ax2=plt.subplot(222)
plt.title('6 point tracks')
for d in dists:
ax2.plot(res[6][d]['time'][:-2],label=str(d*2.5)+' mm')
ax2.set_ylim((0,6000))
ax2.set_xlim((0,9))
ax2.set_xticklabels(['100K','200K','300K','400K','500K','600K','700K','800K','900K','1M'])
ax2.set_ylabel('Seconds')
ax2.set_xlabel('Number of tracks')
plt.legend()
ax3=plt.subplot(223)
plt.title('12 point tracks')
for d in dists:
ax3.plot(res[12][d]['time'][:-2],label=str(d*2.5)+' mm')
ax3.set_ylim((0,6000))
ax3.set_xlim((0,9))
ax3.set_xticklabels(['100K','200K','300K','400K','500K','600K','700K','800K','900K','1M'])
ax3.set_ylabel('Seconds')
ax3.set_xlabel('Number of tracks')
plt.legend()
ax4=plt.subplot(224)
plt.title('18 point tracks')
for d in dists:
ax4.plot(res[18][d]['time'][:-2],label=str(d*2.5)+' mm')
ax4.set_ylim((0,6000))
ax4.set_xlim((0,9))
ax4.set_xticklabels(['100K','200K','300K','400K','500K','600K','700K','800K','900K','1M'])
ax4.set_ylabel('Seconds')
ax4.set_xlabel('Number of tracks')
plt.legend(loc=2)
plt.show()
def show_timing_vs_others():
res=load_pickle('/home/eg309/Data/LSC_limits/timings_1K_100K.pkl')
ax=plt.subplot(111)
times=res[12][8]['time'][:-1]
print len(times)
x=np.arange(10**3,10**5+10**3,10**3)
print len(x)
#ax.set_xticklabels(['1K','20K','40K','60K','70K','80K','90K','100K'])
ax.plot(x,times,label='LSC')
ax.plot([1000,60000],[30,14400],"*",label='Wang')
#ax.set_ylim((0,40))
#ax.set_xlim((1000,100000))
plt.legend(loc=0)
plt.show()
#show_timings()
show_timing_vs_others()