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)