def beta_fitting_python(meta, use_prob_bins): """Induce beta distribution for elicitations about highest/lowest/avg person. Args: meta: np.array of lowest/middle/highest elicitation use_order_stats: True or False, which determines which fractiles used. Returns: np.array where each row contains parameters of beta distributions for each respondent. A row contains -1, -1 if elicitation did not satisy constraints required to produce beta distribn Note: order of meta and fractiles in curve fitting. I originally had these swopped. """ def bcdf(x, bp1, bp2): return jmutils.beta_cdf_two_pts(0, x, bp1, bp2) if use_prob_bins: fractiles = np.array([1/6, .5, 5/6]) else: fractiles = np.array([.2, .5, .8]) meta = meta / 100 #if (meta[1] <= meta[0]) or (meta[2] <= meta[1]): # beta_params = [-1, -1] # print("Warning! Elicited parameters which are not coherent.") # print(meta) #else: meta[0] = jmutils.bound(meta[0], 0.01, 0.99) meta[2] = jmutils.bound(meta[2], 0.01, 0.99) beta_params, pcov = curve_fit(bcdf, meta, fractiles) return beta_params
def calc_easy_bts_binary(responses, meta_true): """Calculate easiest binary version of bts using own answers and predicted percentage of ppl endorsing true Args: responses: list where elt is 0 if subject said false and 1 if subject said true. meta_true: list where elt is subject's prediction of fraction of ppl endorsing true. Returns: dict where each field (bts, surprise, accuracy) points to an np.array with an elt for each subject. """ assert len(responses) == len(meta_true) do_assert = True xbar_true = jmutils.mean(responses) xbar_true = jmutils.bound(xbar_true, 0.01, 0.99) xbar = [1 - xbar_true, xbar_true] meta_true_trimmed = [jmutils.bound(mt, 0.01, 0.99) for mt in meta_true] meta_false = [1 - et for et in meta_true_trimmed] log_ybar = [jmutils.log_geo_mean(meta_false), jmutils.log_geo_mean(meta_true_trimmed)] #if (xbar_true != jmutils.mean(responses)) or (len(responses) == 1): # do_assert = False easy_bts = calc_generic_bts(xbar, log_ybar, responses, zip(meta_false, meta_true_trimmed)) return easy_bts