def disjunction(n=3):
"""Settings for Bergen et al.'s figure 6. Seems to reproduce the effects they report."""
# bl = {'p': [r'$w_1$', r'$w_2$'], 'q':[r'$w_2$', r'$w_3$']}
bl = {'p': ['1', '2'], 'q':['1', '3'], 'p & q': ['1'], 'p v q': ['1', '2', '3']}
lexica = Lexica(baselexicon=bl,
atomic_states=['1', '2', '3'],
disjunction_cost=1.0,
conjunction_cost=0.0,
null_cost=5.0,
join_closure=True,
meet_closure=False,
block_trivial_messages=True,
block_ineffability=False)
lexica.display()
for key, val in lexica.lexica[8].items():
print key, len(val), val
mod = Pragmod(lexica=lexica.lexica2matrices(),
messages=lexica.messages,
meanings=lexica.states,
costs=lexica.cost_vector(),
prior=np.repeat(1.0/len(lexica.states), len(lexica.states)),
lexprior=np.repeat(1.0/len(lexica), len(lexica)),
temperature=1.0,
alpha=1.0)
#mod.plot_expertise_listener(output_filename='../paper/fig/scalardisj-expertise-listener-marginalized.pdf', n=n)
#mod.plot_expertise_speaker(output_filename='../paper/fig/scalardisj-expertise-speaker.pdf', n=n)
#mod.plot_expertise_speaker(output_filename='../paper/fig/scalardisj-expertise-speaker-lexsum.pdf', n=n, lexsum=True)
mod.plot_expertise_listener(n=n)
def manner(n=3):
"""Settings for Bergen et al.'s figure 6. Seems to reproduce the effects they report."""
lexica = Lexica(baselexicon={'SHORT': [r'$w_{RARE}$', r'$w_{FREQ}$'], r'long': [r'$w_{RARE}$', r'$w_{FREQ}$']},
costs={'SHORT':1.0, r'long':2.0},
null_cost=5.0,
join_closure=False,
disjunction_cost=0.1)
lexica.display()
mod = Pragmod(lexica=lexica.lexica2matrices(),
messages=lexica.messages,
meanings=lexica.states,
costs=lexica.cost_vector(),
prior=np.array([2.0/3.0, 1.0/3.0]),
lexprior=np.repeat(1.0/len(lexica), len(lexica)),
temperature=1.0,
alpha=3.0)
mod.plot_expertise_listener(output_filename='../paper/fig/manner-expertise-listener-marginalized.pdf', n=n)
mod.plot_expertise_speaker(output_filename='../paper/fig/manner-expertise-speaker.pdf', n=n)
mod.plot_expertise_speaker(output_filename='../paper/fig/manner-expertise-speaker-lexsum.pdf', n=n, lexsum=True)
