Error caused by `retest_cnv()` function about numbat HOT 6 CLOSED

# Load a subset of the data. I've removed the "snp_id","POS", "REF", "ALT", "GT"
# & "snp_index" columns and restricted to just chr7. This is sufficient to
# reproduce the original error.
bulk_subset <- read.csv("~/Downloads/bulk_subset.csv")

# Load required functions
devtools::load_all("~/Documents/numbat/")

# Define some required params
G = c('20' = 1/5, '10' = 1/5, '21' = 1/10, '31' = 1/10, '22' = 1/5, '00' = 1/5)
delta_phi_min = 0.15
exp_model = "lnpois"
gamma = 20
theta_min = 0.065

# Produce error
segs_post = bulk_subset %>% 
    filter(cnv_state != 'neu') %>%
    group_by(CHROM, seg, seg_start, seg_end, cnv_state) %>%
    summarise(
        n_genes = length(na.omit(unique(gene))),
        n_snps = sum(!is.na(pAD)),
        theta_hat = theta_hat_seg(major_count[!is.na(major_count)], minor_count[!is.na(minor_count)]),
        approx_theta_post(pAD[!is.na(pAD)], DP[!is.na(pAD)], p_s[!is.na(pAD)], gamma = unique(gamma), start = theta_hat),
        L_y_n = pnorm.range(0, theta_min, theta_mle, theta_sigma),
        L_y_d = pnorm.range(theta_min, 0.499, theta_mle, theta_sigma),
        L_y_a = pnorm.range(theta_min, 0.375, theta_mle, theta_sigma),
        approx_phi_post(
            Y_obs[!is.na(Y_obs)], lambda_ref[!is.na(Y_obs)], unique(na.omit(d_obs)),
            alpha = alpha[!is.na(Y_obs)],
            beta = beta[!is.na(Y_obs)],
            mu = mu[!is.na(Y_obs)],
            sig = sig[!is.na(Y_obs)],
            model = exp_model
        ),
        L_x_n = pnorm.range(1 - delta_phi_min, 1 + delta_phi_min, phi_mle, phi_sigma),
        L_x_d = pnorm.range(0.1, 1 - delta_phi_min, phi_mle, phi_sigma),
        L_x_a = pnorm.range(1 + delta_phi_min, 3, phi_mle, phi_sigma),
        Z = sum(G['20'] * L_x_n * L_y_d,
                G['10'] * L_x_d * L_y_d,
                G['21'] * L_x_a * L_y_a,
                G['31'] * L_x_a * L_y_a,
                G['22'] * L_x_a * L_y_n, 
                G['00'] * L_x_d * L_y_n),
        p_loh = (G['20'] * L_x_n * L_y_d)/Z,
        p_amp = ((G['31'] + G['21']) * L_x_a * L_y_a)/Z,
        p_del = (G['10'] * L_x_d * L_y_d)/Z,
        p_bamp = (G['22'] * L_x_a * L_y_n)/Z,
        p_bdel = (G['00'] * L_x_d * L_y_n)/Z,
        LLR_x = calc_exp_LLR(
            Y_obs[!is.na(Y_obs)],
            lambda_ref[!is.na(Y_obs)], 
            unique(na.omit(d_obs)),
            phi_mle,
            alpha = alpha[!is.na(Y_obs)],
            beta = beta[!is.na(Y_obs)],
            mu = mu[!is.na(Y_obs)],
            sig = sig[!is.na(Y_obs)],
            model = exp_model
        ),
        LLR_y = calc_allele_LLR(pAD[!is.na(pAD)], DP[!is.na(pAD)], p_s[!is.na(pAD)], theta_mle, gamma = unique(gamma)),
        LLR = LLR_x + LLR_y,
        .groups = 'drop'
    ) %>%
    rowwise() %>%
    mutate(cnv_state_post = c('loh', 'amp', 'del', 'bamp', 'bdel')[
        which.max(c(p_loh, p_amp, p_del, p_bamp, p_bdel))
    ]) %>%
    ungroup()