def test_gini2shares(self):
gini0 = random.random()
nbrackets = 10 ** random.randrange(3, 5)
shares01 = list(gini2shares(gini=gini0, nbrackets=nbrackets))
print "sum", sum(shares01)
gini1 = calc_gini(shares01)
# print "ginis:", gini0, gini1 TODO: better accuracy expected...
self.assert_(fmath.feq(gini0, gini1, 1e-3)) # imposed and computed Gini shd be equal
print "here"
shares02 = list(gini2sharesPareto(gini=gini0, nbrackets=nbrackets))
print "sum", sum(shares02)
gini2 = calc_gini(shares02)
# print "ginis:", gini0, gini1 TODO: better accuracy expected...
self.assert_(fmath.feq(gini0, gini2, 1.0 / nbrackets)) # imposed and computed Gini shd be equal
"""
def test_gini2shares(self): nshares = 30 test_gini = random.random() shares = list( utilities.gini2sharesPower(test_gini, 30) ) shares02 = np.diff( np.linspace(0, 1, nshares+1)**((1+test_gini)/(1-test_gini)) ) self.assertTrue(np.allclose(shares, shares02)) shares_gini = calc_gini(share*100 for share in shares) #print test_gini, shares_gini #TODO: improve accuracy self.assert_( abs(test_gini - shares_gini ) < 1e-02 )
def test_calc_gini(self):
#test that two Gini formulae give same result
gini1 = calc_gini(self.wealths)
gini2 = calc_gini2(self.wealths)
gini3 = calc_gini3(self.wealths)
gini4 = calc_gini4(self.wealths)
#print "gini1:%f, gini2:%f"%(gini1, gini2)
self.assert_(fmath.feq(gini1, gini2))
self.assert_(fmath.feq(gini1, gini3))
print gini1, gini4
self.assert_(fmath.feq(gini1, gini4))
def test_calc_gini(self):
# test that two Gini formulae give same result
gini1 = calc_gini(self.wealths)
gini2 = calc_gini2(self.wealths)
gini3 = calc_gini3(self.wealths)
gini4 = calc_gini4(self.wealths)
# print "gini1:%f, gini2:%f"%(gini1, gini2)
self.assert_(fmath.feq(gini1, gini2))
self.assert_(fmath.feq(gini1, gini3))
print gini1, gini4
self.assert_(fmath.feq(gini1, gini4))
def record_history(self): #TODO: calc distribution over **indivs** or households??
history = self.history
#compute current wealth distribution
dist = utilities.calc_gini( indiv.calc_wealth() for indiv in self.ppl.gen_indivs() )
history['dist'].append(dist)
history['ppl_size'].append(self.ppl.get_size())
history['capital'].append( self.funds[0].calc_accts_value() )
if hasattr(self.ppl, 'new_cohort_sexes'):
freq = defaultdict(int)
for s in self.ppl.new_cohort_sexes.split(';'):
freq[len(s)] += 1
history['sexes'].append( freq )
def test_gini2shares(self):
gini0 = random.random()
nbrackets = 10**random.randrange(3, 5)
shares01 = list(gini2shares(gini=gini0, nbrackets=nbrackets))
print "sum", sum(shares01)
gini1 = calc_gini(shares01)
#print "ginis:", gini0, gini1 TODO: better accuracy expected...
self.assert_(fmath.feq(gini0, gini1,
1e-3)) #imposed and computed Gini shd be equal
print "here"
shares02 = list(gini2sharesPareto(gini=gini0, nbrackets=nbrackets))
print "sum", sum(shares02)
gini2 = calc_gini(shares02)
#print "ginis:", gini0, gini1 TODO: better accuracy expected...
self.assert_(
fmath.feq(gini0, gini2,
1. / nbrackets)) #imposed and computed Gini shd be equal
print shares01[::100]
print calc_gini(shares01)
print shares02[::100]
print calc_gini(shares02)
fig, (ax1, ax2) = plt.subplots(1, 2)
ax1.plot(shares01)
ax2.plot(np.cumsum(shares01))
ax2.plot(np.cumsum(shares02))
plt.show()
exit()
def record_history(
self): #TODO: calc distribution over **indivs** or households??
history = self.history
#compute current wealth distribution
dist = utilities.calc_gini(indiv.calc_wealth()
for indiv in self.ppl.gen_indivs())
history['dist'].append(dist)
history['ppl_size'].append(self.ppl.get_size())
history['capital'].append(self.funds[0].calc_accts_value())
if hasattr(self.ppl, 'new_cohort_sexes'):
freq = defaultdict(int)
for s in self.ppl.new_cohort_sexes.split(';'):
freq[len(s)] += 1
history['sexes'].append(freq)
def test_gini2shares(self): gini0 = random.random() nbrackets = 10**random.randrange(3,5) shares01 = list(gini2shares(gini=gini0, nbrackets=nbrackets)) print "sum", sum(shares01) gini1 = calc_gini(shares01) #print "ginis:", gini0, gini1 TODO: better accuracy expected... self.assert_(fmath.feq(gini0, gini1, 1e-3)) #imposed and computed Gini shd be equal print "here" shares02 = list( gini2sharesPareto(gini=gini0, nbrackets=nbrackets) ) print "sum", sum(shares02) gini2 = calc_gini(shares02) #print "ginis:", gini0, gini1 TODO: better accuracy expected... self.assert_(fmath.feq(gini0, gini2, 1./nbrackets)) #imposed and computed Gini shd be equal print shares01[::100] print calc_gini(shares01) print shares02[::100] print calc_gini(shares02) fig, (ax1,ax2) = plt.subplots(1,2) ax1.plot(shares01) ax2.plot(np.cumsum(shares01)) ax2.plot(np.cumsum(shares02)) plt.show() exit()
def adjust_kn(self, d, g):
for consumer in self.consumers:
consumer.adjust_kn(d, g)
def get_unemployment(self):
kn = self.kn
return sum(f[1] == 0 for f in kn) / len(kn)
print
# health_threshold currently global: TODO
health_threshold = 1.0
health_threshold = 0.1
consumer = CompositeSolowConsumer(K0, N0)
for _ in range(1000):
K, N = consumer.get_kn()
Y = f(K, N)
#print "K: %5.2f, AN: %5.2f, Y: %5.2f"%(K,N,Y)
#print consumer.kn
if not _ % 50:
print "unemployment: ", consumer.get_unemployment(
), "inequality: ", calc_gini(c.k for c in consumer.consumers)
#print [(c.health < health_threshold) for c in consumer.consumers]
#TODO: d and g and alpha are currently global
consumer.adjust_kn(d, gN + gA) #timing crucial! (fix that?)
consumer.receive(alpha * Y, 'rents')
print
consumer.receive((1 - alpha) * Y, 'wages')
print
def testGini(self): #TODO: move this gini1 = calc_gini(self.wealths) gini2 = calc_gini2(self.wealths) print "gini1:%f, gini2:%f"%(gini1, gini2) self.assert_( abs(gini1-gini2)<1e-8 )
