def __init__(self, relations,
before_dist_1_beginning_dist_2_beginning, same_dist_1_beginning_dist_2_beginning,
before_dist_1_beginning_dist_2_ending, same_dist_1_beginning_dist_2_ending,
before_dist_1_ending_dist_2_beginning, same_dist_1_ending_dist_2_beginning,
before_dist_1_ending_dist_2_ending, same_dist_1_ending_dist_2_ending):
self.relations = relations
self[dist_1_beginning, dist_2_beginning] = (
before_dist_1_beginning_dist_2_beginning,
same_dist_1_beginning_dist_2_beginning
)
self[dist_1_beginning, dist_2_ending] = (
before_dist_1_beginning_dist_2_ending,
same_dist_1_beginning_dist_2_ending
)
self[dist_1_ending, dist_2_beginning] = (
before_dist_1_ending_dist_2_beginning,
same_dist_1_ending_dist_2_beginning
)
self[dist_1_ending, dist_2_ending] = (
before_dist_1_ending_dist_2_ending,
same_dist_1_ending_dist_2_ending
)
self.formula = FormulaCreator(self)
def check(self):
from spatiotemporal.temporal_events import FormulaCreator
print self.data
print FormulaCreator(self).calculate_relations().to_vector()
print
data = []
for key in self.combinations:
before, same, after = self.compare(*key)
data.append(before)
data.append(same)
return data
def check(self):
from spatiotemporal.temporal_events import FormulaCreator
print self.data
print FormulaCreator(self).calculate_relations().to_vector()
print
if __name__ == '__main__':
from spatiotemporal.temporal_events import FormulaCreator
from spatiotemporal.temporal_events.trapezium import generate_random_events
for i in xrange(50):
A, B = generate_random_events(2)
relations = A * B
print relations.to_list()
# from the 13 relations, learns parameters for all combinations of the
# before, same, and after relationships between the beginning and
# ending distributions of the two intervals
formula = FormulaCreator(DecompositionFitter(relations))
# from these relationships, computes the 13 relations again
relations_estimate = formula.calculate_relations()
print relations_estimate.to_list()
print relations.to_vector() - relations_estimate.to_vector()
print
