from nodes import setup, speciesList
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats.stats import pearsonr
tauRange = range(0,101,10)
algPercent = []
currPercent = []
for tau in tauRange:
print tau
algPercent.append([])
currPercent.append([])
for j in range(5):
print "--" + str(j)
photos,users = setup(tau=tau)
for p in photos.values():
p.__sample__(5)
for u in users.values():
u.__prune__()
#initialize things using majority voting
for p in photos.values():
p.__majorityVote__()
#estimate the user's "correctness"
for u in users.values():
for s in speciesList:
u.__speciesCorrect__(s,beta=0.2)
"gazelleGrants": [],
"guineaFowl": [],
"hyenaSpotted": [],
"otherBird": [],
"hippopotamus": [],
"reedbuck": [],
"eland": [],
"baboon": [],
"lionFemale": [],
"topi": []
}
total = {s: 0. for s in correct.keys()}
print len(correct)
for j in range(1):
print j
photos, users = setup(tau=50)
for p in photos.values():
p.__sample__(25)
for u in users.values():
u.__prune__()
#initialize things using majority voting
for p in photos.values():
p.__majorityVote__()
#estimate the user's "correctness"
for u in users.values():
for s in speciesList:
u.__speciesCorrect__(s, beta=0.01)
#!/usr/bin/env python
__author__ = 'greg'
from nodes import setup
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats.stats import pearsonr
photos, users = setup()
for p in photos.values():
p.__majorityVote__()
X = []
Y = []
for u in users.values():
e, h = u.__getStats__()
if (e != -1) and (h != -1):
X.append(e * 100)
Y.append(h * 100)
plt.plot(X, Y, '.', color="black")
plt.xlabel("Percentage of easy pictures correctly classified")
plt.ylabel("Percentage of hard pictures correctly classified")
print pearsonr(X, Y)
plt.show()
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats.stats import pearsonr
numUser = [5, 10, 15, 20, 25]
tauRange = [1, 10, 100]
algPercent = {t: [] for t in tauRange}
for nn in numUser:
print nn
for t in tauRange:
algPercent[t].append([])
for j in range(10):
print "== " + str(j)
photos, users = setup(tau=10)
for p in photos.values():
p.__sample__(nn)
for u in users.values():
u.__prune__()
#initialize things using majority voting
for p in photos.values():
p.__majorityVote__()
for t in tauRange:
#estimate the user's "correctness"
for u in users.values():
for s in speciesList:
#!/usr/bin/env python
__author__ = 'greg'
from nodes import setup
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats.stats import pearsonr
photos,users = setup()
for p in photos.values():
p.__majorityVote__()
X = []
Y = []
for u in users.values():
e,h = u.__getStats__()
if (e != -1) and (h != -1):
X.append(e*100)
Y.append(h*100)
plt.plot(X,Y,'.',color="black")
plt.xlabel("Percentage of easy pictures correctly classified")
plt.ylabel("Percentage of hard pictures correctly classified")
print pearsonr(X,Y)
plt.show()
from nodes import setup, speciesList
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats.stats import pearsonr
tauRange = range(0, 101, 10)
algPercent = []
currPercent = []
for tau in tauRange:
print tau
algPercent.append([])
currPercent.append([])
for j in range(5):
print "--" + str(j)
photos, users = setup(tau=tau)
for p in photos.values():
p.__sample__(5)
for u in users.values():
u.__prune__()
#initialize things using majority voting
for p in photos.values():
p.__majorityVote__()
#estimate the user's "correctness"
for u in users.values():
for s in speciesList:
u.__speciesCorrect__(s, beta=0.2)
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats.stats import pearsonr
numUser = [5,10,15,20,25]
algPercent = []
currPercent = []
speciesList = ['elephant','zebra','warthog','impala','buffalo','wildebeest','gazelleThomsons','dikDik','giraffe','gazelleGrants','lionFemale','baboon','hippopotamus','ostrich','human','otherBird','hartebeest','secretaryBird','hyenaSpotted','mongoose','reedbuck','topi','guineaFowl','eland','aardvark','lionMale','porcupine','koriBustard','bushbuck','hyenaStriped','jackal','cheetah','waterbuck','leopard','reptiles','serval','aardwolf','vervetMonkey','rodents','honeyBadger','batEaredFox','rhinoceros','civet','genet','zorilla','hare','caracal','wildcat']
correct = {"wildebeest":[],"zebra":[],"hartebeest":[],"gazelleThomsons":[],"buffalo":[],"impala":[],"warthog":[],"giraffe":[],"elephant":[],"human":[],"gazelleGrants":[],"guineaFowl":[],"hyenaSpotted":[],"otherBird":[],"hippopotamus":[],"reedbuck":[],"eland":[],"baboon":[],"lionFemale":[],"topi":[]}
total = {s:0. for s in correct.keys()}
print len(correct)
for j in range(1):
print j
photos,users = setup(tau=50)
for p in photos.values():
p.__sample__(25)
for u in users.values():
u.__prune__()
#initialize things using majority voting
for p in photos.values():
p.__majorityVote__()
#estimate the user's "correctness"
for u in users.values():
for s in speciesList:
u.__speciesCorrect__(s,beta=0.01)
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats.stats import pearsonr
numUser = [5,10,15,20,25]
tauRange = [1,10,100]
algPercent = {t:[] for t in tauRange}
for nn in numUser:
print nn
for t in tauRange:
algPercent[t].append([])
for j in range(10):
print "== " + str(j)
photos,users = setup(tau=10)
for p in photos.values():
p.__sample__(nn)
for u in users.values():
u.__prune__()
#initialize things using majority voting
for p in photos.values():
p.__majorityVote__()
for t in tauRange:
#estimate the user's "correctness"
for u in users.values():
