def t7():
input_8 = [0.75, 0.2, 0.2, 0.1, 0.5]
epsilon_8 = 0.1
delta_8 = 0.1
output_8 = chowreconstruct.cr1(input_8, epsilon_8, delta_8)
print(output_8)
print(exact_chow(output_8))
def t8():
weights = generate_sample_weights(4, 0, 10)
print(weights)
chow_params = exact_chow(weights)
print(chow_params)
output_9 = chowreconstruct.cr1(chow_params, 0.15, 0.1)
print(output_9)
c_p_output = exact_chow(output_9)
print(c_p_output)
def t_n(n, x):
for i in range(0, x):
weights = generate_sample_weights(n, 0, 10)
chow_params = exact_chow(weights)
output = chowreconstruct.cr1(chow_params, 0.15, 0.1)
chow_output = exact_chow(output)
distance = chowreconstruct.l2_distance(chow_params, chow_output)
if distance > 0.15:
warnings.warn("failure")
print(chow_params)
print(chow_output)
def t6():
input_7 = [0.75, 0.25, 0.25, 0.25]
epsilon_7 = 0.1
delta_7 = 0.1
m_7 = 14023
n_7 = 4
output_7 = chowreconstruct.cr1(input_7, epsilon_7, delta_7)
print(output_7)
output_8 = chowreconstruct.approximate(output_7, m_7, n_7)
assert(output_8[0] - input_7[0] < 0.1)
assert(output_8[1] - input_7[1] < 0.1)
assert(output_8[2] - input_7[2] < 0.1)
assert(output_8[3] - input_7[3] < 0.1)
