def process_galaxies(galaxies):
pdfs = clf.predict_proba(galaxies[parameters].values) / 0.01
cos_t_samples = []
index = 0
for i, galaxy in galaxies.iterrows():
xz_kde = get_xz_kde(PDF(pdfs[index], q_grid), False, 10, 0, 1)
cos_t = sample_cos_t(galaxy["ba"], xz_kde, 10)
cos_t_samples.append(cos_t)
index += 1
return cos_t_samples
def guess_char():
global prev
controller = Leap.Controller()
controller.set_policy(Leap.Controller.POLICY_BACKGROUND_FRAMES)
classes = clf.classes_
probs = zip(
classes,
clf.predict_proba([
v for k, v in get_hand_position(controller, True).iteritems()
])[0])
alpha = max([score for sym, score in probs])
most_probable = sorted([(sym, alpha * score + (1 - alpha))
for sym, score in probs],
key=lambda t: t[1],
reverse=True)
print most_probable[:3]
prev = most_probable[0][0]
print prev
def guess_char():
global prev
controller = Leap.Controller()
controller.set_policy(Leap.Controller.POLICY_BACKGROUND_FRAMES)
classes = clf.classes_
probs = zip(classes, clf.predict_proba([v for k, v in
get_hand_position(controller, True).iteritems()])[0])
alpha = max([score for sym, score in probs])
most_probable = sorted([(sym, alpha * score + (1 - alpha))
for sym, score in probs], key=lambda t: t[1],
reverse=True)
print most_probable[:3]
prev = most_probable[0][0]
print prev