human
Solve the following python programming problem given the following code:
def _log_compare(mat, cats, significance_test = scipy.stats.ttest_ind) : 
    ' Calculates pairwise log ratios between all features and performs a
    significiance test (i.e. t-test) to determine if there is a significant
    difference in feature ratios with respect to the variable of interest.

    Parameters
    ----------
    mat: np.array
       rows correspond to samples and columns correspond to
       features (i.e. OTUs)
    cats: np.array, float
       Vector of categories
    significance_test: function
        statistical test to run

    Returns:
    --------
    log_ratio : np.array
        log ratio pvalue matrix
    ' 
    (r, c) = mat.shape 
    log_ratio = np.zeros ((c, c)) 
    log_mat = np.log (mat) 
    cs = np.unique (cats) 
    def func(x) : 
        return significance_test (* [x [(cats == k)] for k in cs]) 
for i in range ((c - 1)) : 
        ratio = (log_mat [:, i].T - log_mat [:, (i + 1) :].T).T 
        (m, p) = np.apply_along_axis (func, axis = 0, arr = ratio) 
        log_ratio [i, (i + 1) :] = np.squeeze (np.array (significance_test.T)) 
return log_ratio 

    
    

    Fix the buggy line: log_ratio [i, (i + 1) :] = np.squeeze (np.array (significance_test.T))
assistant
#Here is Python code to determine if there is a significant
.

log_ratio [i, (i + 1) :] = np.squeeze (np.array (p.T))