5a04f03e55143925256bf1592a6edeb0612558e3,hicexplorer/hicPCA.py,,main,#Any#,71

Before Change

        copymatrix = deepcopy(corrmatrix)
        for row in range(copymatrix.shape[0]):
            row_value = float(sum(corrmatrix[row, :].tolist()[0]))

            for col in range(copymatrix.shape[1]):
                copymatrix[row, col] = float(corrmatrix[row, col]) - (row_value / corrmatrix.shape[0])

        corrmatrix = cov(copymatrix)

        corrmatrix = convertNansToZeros(csr_matrix(corrmatrix)).todense()

After Change

    start_list = []
    end_list = []
    // PCA is computed per chromosome
    length_chromosome_dict = {}
    for chrname in ma.getChrNames():
        chr_range = ma.getChrBinRange(chrname)
        length_chromosome_dict[chrname] = chr_range[1] - chr_range[0]
    for chrname in ma.getChrNames():
        chr_range = ma.getChrBinRange(chrname)

        submatrix = ma.matrix[chr_range[0]:chr_range[1], chr_range[0]:chr_range[1]]


        exp_obs_matrix_ = exp_obs_matrix(submatrix, length_chromosome_dict)
        exp_obs_matrix_ = convertNansToZeros(csr_matrix(exp_obs_matrix_)).todense()
        pearson_correlation_matrix = np.corrcoef(exp_obs_matrix_)
        pearson_correlation_matrix = convertNansToZeros(csr_matrix(pearson_correlation_matrix)).todense()
        

Instances