npm_modules: Fork bower_components into Polymer 0.4.0 and 0.5.0 versions

bower_components/chartnewjs/Add-ins/stats.js

-
-function stats(data, config) {
-        data.stats = {};
-        if (typeof data.datasets == 'undefined') { // Pie structure;
-                PSbasic(data);
-        } else { // line structure;
-                LSbasic(data);
-                Linear_Regression(data);
-        }
-        replace_stats(data, config);
-        return;
-};
-
-function isStat(val) {
-        if (typeof val == "string") {
-                if (val.indexOf("#") >= 0) return true;
-        }
-        return false;
-};
-
-function Linear_Regression(data) {
-        // compute Means - source of algorithm : http://fr.wikipedia.org/wiki/R%C3%A9gression_lin%C3%A9aire
-        data.stats.linear_regression_count_xPos = 0;
-        data.stats.linear_regression_sum_xPos = 0;
-        data.stats.linear_regression_sum_data = 0;
-        for (var i = 0; i < data.datasets.length; i++) {
-                if (!(typeof data.datasets[i].xPos == "undefined")) {
-                        data.datasets[i].stats.linear_regression_sum_xPos = 0;
-                        data.datasets[i].stats.linear_regression_sum_data = 0;
-                        data.datasets[i].stats.linear_regression_count_xPos = 0;
-                        data.datasets[i].stats.count_data = 0;
-                        for (var j = 0; j < data.datasets[i].data.length; j++) {
-                                if (!(typeof data.datasets[i].data[j] == "undefined") && !(typeof data.datasets[i].xPos[j] == "undefined")) {
-                                        data.stats.linear_regression_count_xPos++;
-                                        data.stats.linear_regression_sum_xPos += data.datasets[i].xPos[j];
-                                        data.stats.linear_regression_sum_data += data.datasets[i].data[j];
-                                        data.datasets[i].stats.linear_regression_count_xPos++;
-                                        data.datasets[i].stats.linear_regression_sum_xPos += data.datasets[i].xPos[j];
-                                        data.datasets[i].stats.linear_regression_sum_data += data.datasets[i].data[j];
-                                }
-                        }
-                        if (data.datasets[i].stats.linear_regression_count_xPos > 0) {
-                                data.datasets[i].stats.linear_regression_mean_xPos = data.datasets[i].stats.linear_regression_sum_xPos / data.datasets[i].stats.linear_regression_count_xPos;
-                                data.datasets[i].stats.linear_regression_mean_data = data.datasets[i].stats.linear_regression_sum_data / data.datasets[i].stats.linear_regression_count_xPos;
-                        }
-                }
-        }
-        // mean;
-        if (data.stats.linear_regression_count_xPos > 0) {
-                data.stats.linear_regression_mean_xPos = data.stats.linear_regression_sum_xPos / data.stats.linear_regression_count_xPos;
-                data.stats.linear_regression_mean_data = data.stats.linear_regression_sum_data / data.stats.linear_regression_count_xPos;
-        }
-        // Covariance - variance;
-        data.stats.linear_regression_covariance = 0;
-        data.stats.linear_regression_variance = 0;
-        for (var i = 0; i < data.datasets.length; i++) {
-                if (!(typeof data.datasets[i].xPos == "undefined")) {
-                        data.datasets[i].stats.linear_regression_covariance = 0;
-                        data.datasets[i].stats.linear_regression_variance = 0;
-                        for (var j = 0; j < data.datasets[i].data.length; j++) {
-                                if (!(typeof data.datasets[i].data[j] == "undefined") && !(typeof data.datasets[i].xPos[j] == "undefined")) {
-                                        data.stats.linear_regression_covariance += (data.datasets[i].xPos[j] - data.stats.linear_regression_mean_xPos) * (data.datasets[i].data[j] - data.stats.linear_regression_mean_data);
-                                        data.stats.linear_regression_variance += (data.datasets[i].xPos[j] - data.stats.linear_regression_mean_xPos) * (data.datasets[i].xPos[j] - data.stats.linear_regression_mean_xPos);
-                                        data.datasets[i].stats.linear_regression_covariance += (data.datasets[i].xPos[j] - data.datasets[i].stats.linear_regression_mean_xPos) * (data.datasets[i].data[j] - data.datasets[i].stats.linear_regression_mean_data);
-                                        data.datasets[i].stats.linear_regression_variance += (data.datasets[i].xPos[j] - data.datasets[i].stats.linear_regression_mean_xPos) * (data.datasets[i].xPos[j] - data.datasets[i].stats.linear_regression_mean_xPos);
-                                }
-                        }
-                        if (data.datasets[i].stats.linear_regression_count_xPos > 0) {
-                                data.datasets[i].stats.linear_regression_covariance /= data.datasets[i].stats.linear_regression_count_xPos;
-                                data.datasets[i].stats.linear_regression_variance /= data.datasets[i].stats.linear_regression_count_xPos;
-                                data.datasets[i].stats.linear_regression_b1 = data.datasets[i].stats.linear_regression_covariance / data.datasets[i].stats.linear_regression_variance;
-                                data.datasets[i].stats.linear_regression_b0 = data.datasets[i].stats.linear_regression_mean_data - data.datasets[i].stats.linear_regression_b1 * data.datasets[i].stats.linear_regression_mean_xPos;
-                        }
-                }
-        }
-        // b1 - b0;
-        if (data.stats.linear_regression_count_xPos > 0) {
-                data.stats.linear_regression_covariance /= data.stats.linear_regression_count_xPos;
-                data.stats.linear_regression_variance /= data.stats.linear_regression_count_xPos;
-                data.stats.linear_regression_b1 = data.stats.linear_regression_covariance / data.stats.linear_regression_variance;
-                data.stats.linear_regression_b0 = data.stats.linear_regression_mean_data - data.stats.linear_regression_b1 * data.stats.linear_regression_mean_xPos;
-        }
-}
-
-function PSbasic(data) {
-        data.stats.sum = 0;
-        data.stats.count_all = 0;
-        data.stats.count_missing = 0;
-        data.stats.count_not_missing = 0;
-        data.stats.mean = undefined;
-        data.stats.sum_square_diff_mean = 0;
-        data.stats.standard_deviation = undefined;
-        data.stats.standard_deviation_estimation = undefined;
-        data.stats.student_t_test = undefined;
-        data.stats.coefficient_variation = undefined;
-        data.stats.data_with_stats = false;
-        for (var i = 0; i < data["length"]; i++) {
-                if (!isStat(data[i].value)) {
-                        (data.stats.count_all) ++;
-                } else data.stats.data_with_stats = true;
-                if (typeof data[i].value == "undefined") {
-                        (data.stats.count_missing) ++;
-                } else if (isStat(data[i].value)) {} else {
-                        (data.stats.count_not_missing) ++;
-                        (data.stats.sum) += 1 * data[i].value;
-                }
-        }
-        if (data.stats.count_not_missing > 0) {
-                data.stats.mean = data.stats.sum / data.stats.count_not_missing;
-        }
-        // sum of (val-mean)2;
-        // sum of (val-mean)3;
-        data.stats.sum_square_diff_mean = 0;
-        data.stats.sum_pow3_diff_mean = 0;
-        data.stats.sum_pow4_diff_mean = 0;
-        for (var i = 0; i < data["length"]; i++) {
-                if (typeof data[i].value != "undefined" && !isStat(data[i].value)) {
-                        data.stats.sum_square_diff_mean += Math.pow(data[i].value - data.stats.mean, 2);
-                        data.stats.sum_pow3_diff_mean += Math.pow(data[i].value - data.stats.mean, 3);
-                        data.stats.sum_pow4_diff_mean += Math.pow(data[i].value - data.stats.mean, 4);
-                }
-        }
-        // standard deviation;
-        if (data.stats.count_not_missing > 0) {
-                data.stats.variance = data.stats.sum_square_diff_mean / data.stats.count_not_missing;
-                data.stats.standard_deviation = Math.sqrt(data.stats.sum_square_diff_mean / data.stats.count_not_missing);
-                data.stats.standard_error_mean = Math.sqrt(data.stats.sum_square_diff_mean) / data.stats.count_not_missing;
-        }
-        // standard deviation estimation;
-        if (data.stats.count_not_missing > 1) {
-                data.stats.standard_deviation_estimation = Math.sqrt(data.stats.sum_square_diff_mean / (data.stats.count_not_missing - 1));
-                if (data.stats.mean > 0) data.stats.coefficient_variation = 100 * data.stats.standard_deviation_estimation / data.stats.mean;
-                if (data.stats.standard_deviation_estimation > 0) data.stats.student_t_test = data.stats.mean / (data.stats.standard_deviation_estimation / Math.sqrt(data.stats.count_not_missing));
-                console.log(data.stats.mean);
-                console.log(data.stats.standard_deviation_estimation);
-                console.log(data.stats.count_not_missing);
-        }
-        // skewness;
-        if (data.stats.count_not_missing > 2) {
-                data.stats.skewness = (data.stats.count_not_missing * data.stats.sum_pow3_diff_mean) / (Math.pow(data.stats.standard_deviation_estimation, 3) * (data.stats.count_not_missing - 1) * (data.stats.count_not_missing - 2));
-        } else {
-                data.stats.skewness = undefined;
-        }
-        // kutosis;
-        if (data.stats.count_not_missing > 3) {
-                data.stats.kurtosis = (data.stats.count_not_missing * (data.stats.count_not_missing + 1) * data.stats.sum_pow4_diff_mean) / (Math.pow(data.stats.standard_deviation_estimation, 4) * (data.stats.count_not_missing - 1) * (data.stats.count_not_missing - 2) * (data.stats.count_not_missing - 3)) - 3 * (data.stats.count_not_missing - 1) * (data.stats.count_not_missing - 1) / ((data.stats.count_not_missing - 2) * (data.stats.count_not_missing - 3));
-        } else {
-                data.stats.kurtosis = undefined;
-        }
-        // ordering stats;
-        var orderStat = new Array();
-        cnt = 0;
-        for (i = 0; i < data.length; i++) {
-                if (typeof data[i].value != "undefined" && !isStat(data[i].value)) {
-                        orderStat[cnt] = {
-                                val: 1 * data[i].value,
-                                one: 1
-                        };
-                        cnt++;
-                }
-        }
-        var setStat = new Array();
-        setStat = Pstats(orderStat, "one");
-        for (i = 0; i < setStat.length; i++) {
-                data.stats.minimum = setStat[i].res.minimum;
-                data.stats.maximum = setStat[i].res.maximum;
-                data.stats.Q0 = setStat[i].res.Q0;
-                data.stats.Q1 = setStat[i].res.Q1;
-                data.stats.Q5 = setStat[i].res.Q5;
-                data.stats.Q10 = setStat[i].res.Q10;
-                data.stats.Q25 = setStat[i].res.Q25;
-                data.stats.Q50 = setStat[i].res.Q50;
-                data.stats.Q75 = setStat[i].res.Q75;
-                data.stats.Q90 = setStat[i].res.Q90;
-                data.stats.Q95 = setStat[i].res.Q95;
-                data.stats.Q99 = setStat[i].res.Q99;
-                data.stats.Q100 = setStat[i].res.Q100;
-                data.stats.median = setStat[i].res.median;
-                data.stats.interquartile_range = data.stats.Q75 - data.stats.Q25;
-        }
-};
-
-function LSbasic(data) {
-        data.stats.sum = 0;
-        data.stats.count_all = 0;
-        data.stats.count_missing = 0;
-        data.stats.count_not_missing = 0;
-        data.stats.mean = undefined;
-        data.stats.sum_square_diff_mean = 0;
-        data.stats.sum_pow3_diff_mean = 0;
-        data.stats.sum_pow4_diff_mean = 0;
-        data.stats.standard_deviation = undefined;
-        data.stats.standard_deviation_estimation = undefined;
-        data.stats.student_t_test = undefined;
-        data.stats.coefficient_variation = undefined;
-        data.stats.data_with_stats = false;
-        data.stats.data_minimum = {};
-        data.stats.data_maximum = {};
-        data.stats.data_Q0 = {};
-        data.stats.data_Q1 = {};
-        data.stats.data_Q5 = {};
-        data.stats.data_Q10 = {};
-        data.stats.data_Q25 = {};
-        data.stats.data_Q50 = {};
-        data.stats.data_Q75 = {};
-        data.stats.data_Q90 = {};
-        data.stats.data_Q95 = {};
-        data.stats.data_Q99 = {};
-        data.stats.data_Q100 = {};
-        data.stats.data_median = {};
-        data.stats.data_sum = {};
-        data.stats.data_count_all = {};
-        data.stats.data_count_missing = {};
-        data.stats.data_count_not_missing = {};
-        data.stats.data_mean = {};
-        data.stats.data_sum_square_diff_mean = {};
-        data.stats.data_sum_pow3_diff_mean = {};
-        data.stats.data_sum_pow4_diff_mean = {};
-        data.stats.data_variance = {};
-        data.stats.data_standard_deviation = {};
-        data.stats.data_standard_error_mean = {};
-        data.stats.data_standard_deviation_estimation = {};
-        data.stats.data_student_t_test = {};
-        data.stats.data_coefficient_variation = {};
-        data.stats.data_skewness = {};
-        data.stats.data_kurtosis = {};
-        data.stats.data_interquartile_range = {};
-        data.stats.max_number_data = 0;
-        data.stats.min_number_data = Number.MAX_VALUE;
-        for (var i = 0; i < data.datasets["length"]; i++) {
-                data.datasets[i].stats = {};
-                data.datasets[i].stats.sum = 0;
-                data.datasets[i].stats.count_all = 0;
-                data.datasets[i].stats.count_missing = 0;
-                data.datasets[i].stats.count_not_missing = 0;
-                data.datasets[i].stats.mean = undefined;
-                data.datasets[i].stats.sum_square_diff_mean = 0;
-                data.datasets[i].stats.sum_pow3_diff_mean = 0;
-                data.datasets[i].stats.sum_pow4_diff_mean = 0;
-                data.datasets[i].stats.standard_deviation = undefined;
-                if (data.datasets[i].data["length"] > data.stats.max_number_data) {
-                        for (var k = data.stats.max_number_data; k < data.datasets[i].data["length"]; k++) {
-                                data.stats.data_sum[k] = 0;
-                                data.stats.data_count_all[k] = 0;
-                                data.stats.data_count_missing[k] = 0;
-                                data.stats.data_count_not_missing[k] = 0;
-                                data.stats.data_mean[k] = undefined;
-                                data.stats.data_sum_square_diff_mean[k] = 0;
-                                data.stats.data_sum_pow3_diff_mean[k] = 0;
-                                data.stats.data_sum_pow4_diff_mean[k] = 0;
-                                data.stats.data_standard_deviation[k] = undefined;
-                                data.stats.data_standard_deviation_estimation[k] = undefined;
-                                data.stats.data_student_t_test[k] = undefined;
-                                data.stats.data_coefficient_variation[k] = undefined;
-                        }
-                        data.stats.max_number_data = data.datasets[i].data["length"];
-                        data.stats.min_number_data = Math.min(data.stats.min_number_data, data.datasets[i].data["length"]);
-                }
-                for (var j = 0; j < data.datasets[i].data["length"]; j++) {
-                        if (!isStat(data.datasets[i].data[j])) {
-                                (data.stats.count_all) ++;
-                                (data.datasets[i].stats.count_all) ++;
-                                (data.stats.data_count_all[j]) ++;
-                        } else {
-                                data.stats.data_with_stats = true;
-                        }
-                        if (typeof data.datasets[i].data[j] == "undefined") {
-                                (data.stats.count_missing) ++;
-                                (data.datasets[i].stats.count_missing) ++;
-                                (data.stats.data_count_missing[j]) ++;
-                        } else if (isStat(data.datasets[i].data[j])) {} else {
-                                (data.stats.count_not_missing) ++;
-                                (data.datasets[i].stats.count_not_missing) ++;
-                                (data.stats.data_count_not_missing[j]) ++;
-                                (data.stats.sum) += 1 * data.datasets[i].data[j];
-                                (data.datasets[i].stats.sum) += 1 * data.datasets[i].data[j];
-                                (data.stats.data_sum[j]) += 1 * data.datasets[i].data[j];
-                        }
-                }
-                if (data.datasets[i].stats.count_not_missing == 0) {
-                        data.datasets[i].stats.minimum = undefined;
-                        data.datasets[i].stats.maximum = undefined;
-                        data.datasets[i].stats.sum = undefined;
-                        data.datasets[i].stats.mean = undefined;
-                } else {
-                        data.datasets[i].stats.mean = data.datasets[i].stats.sum / data.datasets[i].stats.count_not_missing;
-                }
-        }
-        if (data.stats.count_not_missing > 0) {
-                data.stats.mean = data.stats.sum / data.stats.count_not_missing;
-        }
-        for (i = 0; i < data.stats.max_number_data; i++) {
-                if (data.stats.data_count_not_missing[i] > 0) {
-                        data.stats.data_mean[i] = data.stats.data_sum[i] / data.stats.data_count_not_missing[i];
-                }
-        }
-        // sum of (val-mean)2;
-        data.stats.sum_square_diff_mean = 0;
-        data.stats.sum_pow3_diff_mean = 0;
-        data.stats.sum_pow4_diff_mean = 0;
-        for (var i = 0; i < data.datasets["length"]; i++) {
-                data.datasets[i].stats.sum_square_diff_mean = 0;
-                data.datasets[i].stats.sum_pow3_diff_mean = 0;
-                data.datasets[i].stats.sum_pow4_diff_mean = 0;
-                for (var j = 0; j < data.datasets[i].data["length"]; j++) {
-                        if (typeof data.datasets[i].data[j] != "undefined" && !isStat(data.datasets[i].data[j].value)) {
-                                data.stats.sum_square_diff_mean += Math.pow(data.datasets[i].data[j] - data.stats.mean, 2);
-                                data.stats.sum_pow3_diff_mean += Math.pow(data.datasets[i].data[j] - data.stats.mean, 3);
-                                data.stats.sum_pow4_diff_mean += Math.pow(data.datasets[i].data[j] - data.stats.mean, 4);
-                                data.stats.data_sum_square_diff_mean[j] += Math.pow(data.datasets[i].data[j] - data.stats.data_mean[j], 2);
-                                data.stats.data_sum_pow3_diff_mean[j] += Math.pow(data.datasets[i].data[j] - data.stats.data_mean[j], 3);
-                                data.stats.data_sum_pow4_diff_mean[j] += Math.pow(data.datasets[i].data[j] - data.stats.data_mean[j], 4);
-                                data.datasets[i].stats.sum_square_diff_mean += Math.pow(data.datasets[i].data[j] - data.datasets[i].stats.mean, 2);
-                                data.datasets[i].stats.sum_pow3_diff_mean += Math.pow(data.datasets[i].data[j] - data.datasets[i].stats.mean, 3);
-                                data.datasets[i].stats.sum_pow4_diff_mean += Math.pow(data.datasets[i].data[j] - data.datasets[i].stats.mean, 4);
-                        }
-                }
-        }
-        // standard deviation;
-        if (data.stats.count_not_missing > 0) {
-                data.stats.variance = data.stats.sum_square_diff_mean / data.stats.count_not_missing;
-                data.stats.standard_deviation = Math.sqrt(data.stats.sum_square_diff_mean / data.stats.count_not_missing);
-                data.stats.standard_error_mean = Math.sqrt(data.stats.sum_square_diff_mean) / data.stats.count_not_missing;
-        }
-        for (i = 0; i < data.datasets["length"]; i++) {
-                if (data.datasets[i].stats.count_not_missing > 0) {
-                        data.datasets[i].stats.variance = data.datasets[i].stats.sum_square_diff_mean / data.datasets[i].stats.count_not_missing;
-                        data.datasets[i].stats.standard_deviation = Math.sqrt(data.datasets[i].stats.sum_square_diff_mean / data.datasets[i].stats.count_not_missing);
-                        data.datasets[i].stats.standard_error_mean = Math.sqrt(data.datasets[i].stats.sum_square_diff_mean) / data.datasets[i].stats.count_not_missing;
-                }
-        }
-        for (j = 0; j < data.stats.max_number_data; j++) {
-                if (data.stats.data_count_not_missing[j] > 0) {
-                        data.stats.data_variance[j] = data.stats.data_sum_square_diff_mean[j] / data.stats.data_count_not_missing[j];
-                        data.stats.data_standard_deviation[j] = Math.sqrt(data.stats.data_sum_square_diff_mean[j] / data.stats.data_count_not_missing[j]);
-                        data.stats.data_standard_error_mean[j] = Math.sqrt(data.stats.data_sum_square_diff_mean[j]) / data.stats.data_count_not_missing[j];
-                }
-        }
-        // standard deviation estimation;
-        if (data.stats.count_not_missing > 1) {
-                data.stats.standard_deviation_estimation = Math.sqrt(data.stats.sum_square_diff_mean / (data.stats.count_not_missing - 1));
-                if (data.stats.mean > 0) data.stats.coefficient_variation = 100 * data.stats.standard_deviation_estimation / data.stats.mean;
-                if (data.stats.standard_deviation_estimation > 0) data.stats.student_t_test = data.stats.mean / (data.stats.standard_deviation_estimation / Math.sqrt(data.stats.count_not_missing));
-        }
-        for (i = 0; i < data.datasets["length"]; i++) {
-                if (data.datasets[i].stats.count_not_missing > 1) {
-                        data.datasets[i].stats.standard_deviation_estimation = Math.sqrt(data.datasets[i].stats.sum_square_diff_mean / (data.datasets[i].stats.count_not_missing - 1));
-                        if (data.datasets[i].stats.mean > 0) data.datasets[i].stats.coefficient_variation = 100 * data.datasets[i].stats.standard_deviation_estimation / data.datasets[i].stats.mean;
-                        if (data.datasets[i].stats.standard_deviation_estimation > 0) data.datasets[i].stats.student_t_test = data.datasets[i].stats.mean / (data.datasets[i].stats.standard_deviation_estimation / Math.sqrt(data.datasets[i].stats.count_not_missing));
-                }
-        }
-        for (j = 0; j < data.stats.max_number_data; j++) {
-                if (data.stats.data_count_not_missing[j] > 1) {
-                        data.stats.data_standard_deviation_estimation[j] = Math.sqrt(data.stats.data_sum_square_diff_mean[j] / (data.stats.data_count_not_missing[j] - 1));
-                        if (data.stats.data_mean[j] > 0) data.stats.data_coefficient_variation[j] = 100 * data.stats.data_standard_deviation_estimation[j] / data.stats.data_mean[j];
-                        if (data.stats.data_standard_deviation_estimation[j] > 0) data.stats.data_student_t_test[j] = data.stats.data_mean[j] / (data.stats.data_standard_deviation_estimation[j] / Math.sqrt(data.stats.data_count_not_missing[j]));
-                }
-        }
-        // skewness;
-        if (data.stats.count_not_missing >= 2) {
-                data.stats.skewness = (data.stats.count_not_missing * data.stats.sum_pow3_diff_mean) / (Math.pow(data.stats.standard_deviation_estimation, 3) * (data.stats.count_not_missing - 1) * (data.stats.count_not_missing - 2));
-        } else {
-                data.stats.skewness = undefined;
-        }
-        // kurtosis;
-        if (data.stats.count_not_missing >= 3) {
-                data.stats.kurtosis = (data.stats.count_not_missing * (data.stats.count_not_missing + 1) * data.stats.sum_pow4_diff_mean) / (Math.pow(data.stats.standard_deviation_estimation, 4) * (data.stats.count_not_missing - 1) * (data.stats.count_not_missing - 2) * (data.stats.count_not_missing - 3)) - 3 * (data.stats.count_not_missing - 1) * (data.stats.count_not_missing - 1) / ((data.stats.count_not_missing - 2) * (data.stats.count_not_missing - 3));
-        } else {
-                data.stats.kurtosis = undefined;
-        }
-        for (i = 0; i < data.datasets["length"]; i++) {
-                if (data.datasets[i].stats.count_not_missing >= 2) {
-                        data.datasets[i].stats.skewness = (data.datasets[i].stats.count_not_missing * data.datasets[i].stats.sum_pow3_diff_mean) / (Math.pow(data.datasets[i].stats.standard_deviation_estimation, 3) * (data.datasets[i].stats.count_not_missing - 1) * (data.datasets[i].stats.count_not_missing - 2));
-                } else {
-                        data.datasets[i].stats.skewness = undefined;
-                }
-                if (data.datasets[i].stats.count_not_missing >= 3) {
-                        data.datasets[i].stats.kurtosis = (data.datasets[i].stats.count_not_missing * (data.datasets[i].stats.count_not_missing + 1) * data.datasets[i].stats.sum_pow4_diff_mean) / (Math.pow(data.datasets[i].stats.standard_deviation_estimation, 4) * (data.datasets[i].stats.count_not_missing - 1) * (data.datasets[i].stats.count_not_missing - 2) * (data.datasets[i].stats.count_not_missing - 3)) - 3 * (data.datasets[i].stats.count_not_missing - 1) * (data.datasets[i].stats.count_not_missing - 1) / ((data.datasets[i].stats.count_not_missing - 2) * (data.datasets[i].stats.count_not_missing - 3));
-                } else {
-                        data.datasets[i].stats.kurtosis = undefined;
-                }
-        }
-        for (j = 0; j < data.stats.max_number_data; j++) {
-                if (data.stats.data_count_not_missing[j] >= 2) {
-                        data.stats.data_skewness[j] = (data.stats.data_count_not_missing[j] * data.stats.data_sum_pow3_diff_mean[j]) / (Math.pow(data.stats.data_standard_deviation_estimation[j], 3) * (data.stats.data_count_not_missing[j] - 1) * (data.stats.data_count_not_missing[j] - 2));
-                } else {
-                        data.stats.data_skewness[j] = undefined;
-                }
-                if (data.stats.data_count_not_missing[j] >= 3) {
-                        data.stats.data_kurtosis[j] = (data.stats.data_count_not_missing[j] * (data.stats.data_count_not_missing[j] + 1) * data.stats.data_sum_pow4_diff_mean[j]) / (Math.pow(data.stats.data_standard_deviation_estimation[j], 4) * (data.stats.data_count_not_missing[j] - 1) * (data.stats.data_count_not_missing[j] - 2) * (data.stats.data_count_not_missing[j] - 3)) - 3 * (data.stats.data_count_not_missing[j] - 1) * (data.stats.data_count_not_missing[j] - 1) / ((data.stats.data_count_not_missing[j] - 2) * (data.stats.data_count_not_missing[j] - 3));
-                } else {
-                        data.stats.data_kurtosis[j] = undefined;
-                }
-        }
-        // ordering stats;
-        var orderStat = new Array();
-        cnt = 0;
-        for (i = 0; i < data.datasets["length"]; i++) {
-                for (j = 0; j < data.datasets[i].data["length"]; j++) {
-                        if (typeof data.datasets[i].data[j] != "undefined" && !isStat(data.datasets[i].data[j].value)) {
-                                orderStat[cnt] = {
-                                        val: 1 * data.datasets[i].data[j],
-                                        dataset: i,
-                                        col: j,
-                                        one: 1
-                                };
-                                cnt++;
-                        }
-                }
-        }
-        var setStat = new Array();
-        setStat = Pstats(orderStat, "one");
-        for (i = 0; i < setStat.length; i++) {
-                data.stats.minimum = setStat[i].res.minimum;
-                data.stats.maximum = setStat[i].res.maximum;
-                data.stats.Q0 = setStat[i].res.Q0;
-                data.stats.Q1 = setStat[i].res.Q1;
-                data.stats.Q5 = setStat[i].res.Q5;
-                data.stats.Q10 = setStat[i].res.Q10;
-                data.stats.Q25 = setStat[i].res.Q25;
-                data.stats.Q50 = setStat[i].res.Q50;
-                data.stats.Q75 = setStat[i].res.Q75;
-                data.stats.Q90 = setStat[i].res.Q90;
-                data.stats.Q95 = setStat[i].res.Q95;
-                data.stats.Q99 = setStat[i].res.Q99;
-                data.stats.Q100 = setStat[i].res.Q100;
-                data.stats.median = setStat[i].res.median;
-                data.stats.interquartile_range = data.stats.Q75 - data.stats.Q25;
-        }
-        setStat = Pstats(orderStat, "dataset");
-        for (i = 0; i < setStat.length; i++) {
-                data.datasets[setStat[i].secvalue].stats.minimum = setStat[i].res.minimum;
-                data.datasets[setStat[i].secvalue].stats.maximum = setStat[i].res.maximum;
-                data.datasets[setStat[i].secvalue].stats.Q0 = setStat[i].res.Q0;
-                data.datasets[setStat[i].secvalue].stats.Q1 = setStat[i].res.Q1;
-                data.datasets[setStat[i].secvalue].stats.Q5 = setStat[i].res.Q5;
-                data.datasets[setStat[i].secvalue].stats.Q10 = setStat[i].res.Q10;
-                data.datasets[setStat[i].secvalue].stats.Q25 = setStat[i].res.Q25;
-                data.datasets[setStat[i].secvalue].stats.Q50 = setStat[i].res.Q50;
-                data.datasets[setStat[i].secvalue].stats.Q75 = setStat[i].res.Q75;
-                data.datasets[setStat[i].secvalue].stats.Q90 = setStat[i].res.Q90;
-                data.datasets[setStat[i].secvalue].stats.Q95 = setStat[i].res.Q95;
-                data.datasets[setStat[i].secvalue].stats.Q99 = setStat[i].res.Q99;
-                data.datasets[setStat[i].secvalue].stats.Q100 = setStat[i].res.Q100;
-                data.datasets[setStat[i].secvalue].stats.median = setStat[i].res.median;
-                data.datasets[setStat[i].secvalue].stats.interquartile_range = data.datasets[setStat[i].secvalue].stats.Q75 - data.datasets[setStat[i].secvalue].stats.Q25;
-        }
-        setStat = Pstats(orderStat, "col");
-        for (i = 0; i < setStat.length; i++) {
-                data.stats.data_minimum[setStat[i].secvalue] = setStat[i].res.minimum;
-                data.stats.data_maximum[setStat[i].secvalue] = setStat[i].res.maximum;
-                data.stats.data_Q0[setStat[i].secvalue] = setStat[i].res.Q0;
-                data.stats.data_Q1[setStat[i].secvalue] = setStat[i].res.Q1;
-                data.stats.data_Q5[setStat[i].secvalue] = setStat[i].res.Q5;
-                data.stats.data_Q10[setStat[i].secvalue] = setStat[i].res.Q10;
-                data.stats.data_Q25[setStat[i].secvalue] = setStat[i].res.Q25;
-                data.stats.data_Q50[setStat[i].secvalue] = setStat[i].res.Q50;
-                data.stats.data_Q75[setStat[i].secvalue] = setStat[i].res.Q75;
-                data.stats.data_Q90[setStat[i].secvalue] = setStat[i].res.Q90;
-                data.stats.data_Q95[setStat[i].secvalue] = setStat[i].res.Q95;
-                data.stats.data_Q99[setStat[i].secvalue] = setStat[i].res.Q99;
-                data.stats.data_Q100[setStat[i].secvalue] = setStat[i].res.Q100;
-                data.stats.data_median[setStat[i].secvalue] = setStat[i].res.median;
-                data.stats.data_interquartile_range[setStat[i].secvalue] = data.stats.data_Q75[setStat[i].secvalue] - data.stats.data_Q25[setStat[i].secvalue];
-        }
-};
-
-function Pstats(orderStat, secVar) {
-        var result = new Array();
-        orderStat.sort(function(a, b) {
-                if (a[secVar] < b[secVar]) return -1
-                else if (a[secVar] > b[secVar]) return 1
-                if (a.val < b.val) return -1
-                else if (a.val > b.val) return 1
-                else return 0
-        });
-        var deb = 0,
-                fin = 0;
-        for (i = 1; i < orderStat.length; i++) {
-                if (orderStat[i][secVar] == orderStat[deb][secVar]) fin++;
-                else {
-                        result[result.length] = {
-                                secvalue: orderStat[deb][secVar],
-                                res: P2stats(deb, fin, orderStat)
-                        };
-                        fin++;
-                        deb = fin;
-                }
-        }
-        result[result.length] = {
-                secvalue: orderStat[deb][secVar],
-                res: P2stats(deb, fin, orderStat)
-        };
-        return result;
-};
-
-function P2stats(deb, fin, orderStat) {
-        return {
-                minimum: orderStat[deb].val,
-                maximum: orderStat[fin].val,
-                Q0: orderStat[deb].val,
-                Q1: Quantile(1, deb, fin, orderStat),
-                Q5: Quantile(5, deb, fin, orderStat),
-                Q10: Quantile(10, deb, fin, orderStat),
-                Q25: Quantile(25, deb, fin, orderStat),
-                Q50: Quantile(50, deb, fin, orderStat),
-                Q75: Quantile(75, deb, fin, orderStat),
-                Q90: Quantile(90, deb, fin, orderStat),
-                Q95: Quantile(95, deb, fin, orderStat),
-                Q99: Quantile(99, deb, fin, orderStat),
-                Q100: orderStat[fin].val,
-                median: Quantile(50, deb, fin, orderStat)
-        }
-};
-
-function Quantile(quant, deb, fin, orderStat) {
-        var nbobs = fin - deb + 1;
-        if (quant <= 50.01) {
-                var v1 = Math.ceil((nbobs * quant / 100) - 0.000001) - 1;
-                var v2 = Math.ceil(((nbobs + 1) * quant / 100) - 0.000001) - 1;
-        } else {
-                var v1 = Math.ceil((nbobs * (100 - quant) / 100) - 0.000001) - 1;
-                v1 = nbobs - v1 - 1;
-                var v2 = Math.ceil(((nbobs + 1) * (100 - quant) / 100) - 0.000001) - 1;
-                v2 = nbobs - v2 - 1;
-        }
-        //  if(deb+v2>fin)v2=fin-deb-1;
-        return ((orderStat[deb + v1].val + orderStat[deb + v2].val) / 2);
-};
-
-function disp_stats(data) {
-        document.write("data.stats.count_all=" + data.stats.count_all + "<BR>");
-        document.write("data.stats.count_missing=" + data.stats.count_missing + "<BR>");
-        document.write("data.stats.count_not_missing=" + data.stats.count_not_missing + "<BR>");
-        document.write("data.stats.minimum=" + data.stats.minimum + "<BR>");
-        document.write("data.stats.maximum=" + data.stats.maximum + "<BR>");
-        document.write("data.stats.sum=" + data.stats.sum + "<BR>");
-        document.write("data.stats.mean=" + data.stats.mean + "<BR>");
-        document.write("data.stats.sum_square_diff_mean=" + data.stats.sum_square_diff_mean + "<BR>");
-        document.write("data.stats.variance=" + data.stats.variance + "<BR>");
-        document.write("data.stats.standard _deviation=" + data.stats.standard_deviation + "<BR>");
-        document.write("data.stats.standard_error_mean=" + data.stats.standard_error_mean + "<BR>");
-        document.write("data.stats.standard_deviation_estimation=" + data.stats.standard_deviation_estimation + "<BR>");
-        document.write("data.stats.coefficient_variation=" + data.stats.coefficient_variation + "<BR>");
-        document.write("data.stats.skewness=" + data.stats.skewness + "<BR>");
-        document.write("data.stats.kurtosis=" + data.stats.kurtosis + "<BR>");
-        document.write("data.stats.student_t_test=" + data.stats.student_t_test + "<BR>");
-        document.write("data.stats.Q0" + data.stats.Q0 + "<BR>");
-        document.write("data.stats.Q1=" + data.stats.Q1 + "<BR>");
-        document.write("data.stats.Q5=" + data.stats.Q5 + "<BR>");
-        document.write("data.stats.Q10=" + data.stats.Q10 + "<BR>");
-        document.write("data.stats.Q25=" + data.stats.Q25 + "<BR>");
-        document.write("data.stats.Q50=" + data.stats.Q50 + "<BR>");
-        document.write("data.stats.Q75=" + data.stats.Q75 + "<BR>");
-        document.write("data.stats.Q90=" + data.stats.Q90 + "<BR>");
-        document.write("data.stats.Q95=" + data.stats.Q95 + "<BR>");
-        document.write("data.stats.Q99=" + data.stats.Q99 + "<BR>");
-        document.write("data.stats.Q100=" + data.stats.Q100 + "<BR>");
-        document.write("data.stats.median=" + data.stats.median + "<BR>");
-        document.write("data.stats.interquartile_range=" + data.stats.interquartile_range + "<BR>");
-        document.write("<hr>")
-        if (typeof data.datasets != 'undefined') {
-                for (i = 0; i < data.datasets.length; i++) {
-                        document.write("<hr>")
-                        document.write("DATASET: " + i + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.count_all=" + data.datasets[i].stats.count_all + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.count_missing=" + data.datasets[i].stats.count_missing + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.count_not_missing=" + data.datasets[i].stats.count_not_missing + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.minimum=" + data.datasets[i].stats.minimum + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.maximum=" + data.datasets[i].stats.maximum + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.sum=" + data.datasets[i].stats.sum + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.mean=" + data.datasets[i].stats.mean + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.sum_square_diff_mean=" + data.datasets[i].stats.sum_square_diff_mean + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.variance=" + data.datasets[i].stats.variance + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.standard_deviation=" + data.datasets[i].stats.standard_deviation + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.standard_error_mean=" + data.datasets[i].stats.standard_error_mean + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.standard_deviation_estimation=" + data.datasets[i].stats.standard_deviation_estimation + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.student_t_test=" + data.datasets[i].stats.student_t_test + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.coefficient_variation=" + data.datasets[i].stats.coefficient_variation + "<BR>");
-                        document.write("data.datasets[" + i + "]stats.skewness=" + data.datasets[i].stats.skewness + "<BR>");
-                        document.write("data.datasets[" + i + "]stats.kurtosis=" + data.datasets[i].stats.kurtosis + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.Q0=" + data.datasets[i].stats.Q0 + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.Q1=" + data.datasets[i].stats.Q1 + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.Q5=" + data.datasets[i].stats.Q5 + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.Q10=" + data.datasets[i].stats.Q10 + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.Q25=" + data.datasets[i].stats.Q25 + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.Q50=" + data.datasets[i].stats.Q50 + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.Q75=" + data.datasets[i].stats.Q75 + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.Q90=" + data.datasets[i].stats.Q90 + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.Q95=" + data.datasets[i].stats.Q95 + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.Q99=" + data.datasets[i].stats.Q99 + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.Q100=" + data.datasets[i].stats.Q100 + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.median=" + data.datasets[i].stats.median + "<BR>");
-                        document.write("data.datasets[" + i + "].stats.interquartile_range=" + data.datasets[i].stats.interquartile_range + "<BR>");
-                }
-                document.write("<hr>")
-                for (i = 0; i < data.stats.max_number_data; i++) {
-                        document.write("<hr>")
-                        document.write("Data: " + i + "<BR>");
-                        document.write("data.stats.data_count_all[" + i + "]=" + data.stats.data_count_all[i] + "<BR>");
-                        document.write("data.stats.data_count_missing[" + i + "]=" + data.stats.data_count_missing[i] + "<BR>");
-                        document.write("data.stats.data_count_not_missing[" + i + "]=" + data.stats.data_count_not_missing[i] + "<BR>");
-                        document.write("data.stats.data_minimum[" + i + "]=" + data.stats.data_minimum[i] + "<BR>");
-                        document.write("data.stats.data_maximum[" + i + "]=" + data.stats.data_maximum[i] + "<BR>");
-                        document.write("data.stats.data_sum[" + i + "]=" + data.stats.data_sum[i] + "<BR>");
-                        document.write("data.stats.data_mean[" + i + "]=" + data.stats.data_mean[i] + "<BR>");
-                        document.write("data.stats.data_sum_square_diff_mean[" + i + "]=" + data.stats.data_sum_square_diff_mean[i] + "<BR>");
-                        document.write("data.stats.data_variance[" + i + "]=" + data.stats.data_variance[i] + "<BR>");
-                        document.write("data.stats.data_standard_deviation[" + i + "]=" + data.stats.data_standard_deviation[i] + "<BR>");
-                        document.write("data.stats.data_standard_error_mean[" + i + "]=" + data.stats.data_standard_error_mean[i] + "<BR>");
-                        document.write("data.stats.data_standard_deviation_estimation[" + i + "]=" + data.stats.data_standard_deviation_estimation[i] + "<BR>");
-                        document.write("data.stats.data_student_t_test[" + i + "]=" + data.stats.data_student_t_test[i] + "<BR>");
-                        document.write("data.stats.data_coefficient_variation[" + i + "]=" + data.stats.data_coefficient_variation[i] + "<BR>");
-                        document.write("data.stats.data_skewness[" + i + "]=" + data.stats.data_skewness[i] + "<BR>");
-                        document.write("data.stats.data_kurtosis[" + i + "]=" + data.stats.data_kurtosis[i] + "<BR>");
-                        document.write("data.stats.data_Q0[" + i + "]=" + data.stats.data_Q0[i] + "<BR>");
-                        document.write("data.stats.data_Q1[" + i + "]=" + data.stats.data_Q1[i] + "<BR>");
-                        document.write("data.stats.data_Q5[" + i + "]=" + data.stats.data_Q5[i] + "<BR>");
-                        document.write("data.stats.data_Q10[" + i + "]=" + data.stats.data_Q10[i] + "<BR>");
-                        document.write("data.stats.data_Q25[" + i + "]=" + data.stats.data_Q25[i] + "<BR>");
-                        document.write("data.stats.data_Q50[" + i + "]=" + data.stats.data_Q50[i] + "<BR>");
-                        document.write("data.stats.data_Q75[" + i + "]=" + data.stats.data_Q75[i] + "<BR>");
-                        document.write("data.stats.data_Q90[" + i + "]=" + data.stats.data_Q90[i] + "<BR>");
-                        document.write("data.stats.data_Q95[" + i + "]=" + data.stats.data_Q95[i] + "<BR>");
-                        document.write("data.stats.data_Q99[" + i + "]=" + data.stats.data_Q99[i] + "<BR>");
-                        document.write("data.stats.data_Q100[" + i + "]=" + data.stats.data_Q100[i] + "<BR>");
-                        document.write("data.stats.data_median[" + i + "]=" + data.stats.data_median[i] + "<BR>");
-                        document.write("data.stats.data_interquartile_range[" + i + "]=" + data.stats.data_interquartile_range[i] + "<BR>");
-                }
-        }
-};
-
-function replace_stats(data, config) {
-        // replace in the data
-        if (data.stats.data_with_stats) {
-                if (typeof data.datasets == 'undefined') { // Pie structure;
-                        for (i = 0; i < data.length; i++) {
-                                if (isStat(data[i].value)) data[i].value = replace_Stats_In(data[i].value, data, -1, -1);
-                                // templates ?
-                                if (isTemplate(data[i].value)) {
-                                        data[i].value = tmplStat(data[i].value, {
-                                                V1: 1
-                                        });
-                                }
-                        }
-                } else { // line structure;
-                        for (var i = 0; i < data.datasets["length"]; i++) {
-                                for (var j = 0; j < data.datasets[i].data["length"]; j++) {
-                                        if (isStat(data.datasets[i].data[j])) {
-                                                data.datasets[i].data[j] = replace_Stats_In(data.datasets[i].data[j], data, i, j);
-                                        }
-                                        // templates ?
-                                        if (isTemplate(data.datasets[i].data[j])) {
-                                                data.datasets[i].data[j] = tmplStat(data.datasets[i].data[j], {
-                                                        V1: 1
-                                                });
-                                        }
-                                }
-                        }
-                }
-        }
-        // replace in other part of the data (titles)
-        if (typeof data.datasets == 'undefined') { // Pie structure;
-                for (i = 0; i < data.length; i++) {
-                        if (isStat(data[i].title)) data[i].title = replace_Stats_In(data[i].title, data, -1, -1);
-                        // templates ?
-                        if (isTemplate(data[i].title)) {
-                                data[i].title = tmplStat(data[i].title, {
-                                        V1: 1
-                                });
-                        }
-                }
-        } else { // line structure;
-                for (var i = 0; i < data.datasets["length"]; i++) {
-                        if (isStat(data.datasets[i].title)) {
-                                data.datasets[i].title = replace_Stats_In(data.datasets[i].title, data, i, -1);
-                        }
-                        // templates ?
-                        if (isTemplate(data.datasets[i].title)) {
-                                data.datasets[i].title = tmplStat(data.datasets[i].title, {
-                                        V1: 1
-                                });
-                        }
-                }
-        }
-        // replace in options
-        replace_in_object(config, data);
-};
-
-function replace_in_object(obj, data) {
-        for (var attrname in obj) {
-                if (typeof obj[attrname] == "object") {
-                        replace_in_object(obj[attrname], data);
-                } else if (isStat(obj[attrname])) {
-                        obj[attrname] = replace_Stats_In(obj[attrname], data, -1, -1);
-                        // templates if not a template option....
-                        if (!(attrname == "annotateLabel" || attrname == "inGraphDataTmpl" || attrname == "scaleLabel")) {
-                                if (isTemplate(obj[attrname])) {
-                                        obj[attrname] = tmplStat(obj[attrname], {
-                                                V1: 1
-                                        });
-                                }
-                        }
-                }
-        }
-};
-
-function tmplStat(str, data) {
-        // Figure out if we're getting a template, or if we need to
-        // load the template - and be sure to cache the result.
-        var fn = !/\W/.test(str) ?
-                cachebis[str] = cachebis[str] ||
-                tmplbis(document.getElementById(str).innerHTML) :
-                // Generate a reusable function that will serve as a template
-                // generator (and which will be cached).
-                new Function("obj",
-                        "var p=[],print=function(){p.push.apply(p,arguments);};" +
-                        // Introduce the data as local variables using with(){}
-                        "with(obj){p.push('" +
-                        // Convert the template into pure JavaScript
-                        str
-                        .replace(/[\r\t\n]/g, " ")
-                        .split("<%").join("\t")
-                        .replace(/((^|%>)[^\t]*)'/g, "$1\r")
-                        .replace(/\t=(.*?)%>/g, "',$1,'")
-                        .split("\t").join("');")
-                        .split("%>").join("p.push('")
-                        .split("\r").join("\\'") + "');}return p.join('');");
-        // Provide some basic currying to the user
-        return data ? fn(data) : fn;
-};
-
-function isTemplate(strvar) {
-        if (typeof strvar == "string") {
-                if (strvar.indexOf("<%") >= 0) {
-                        if (strvar.indexOf(">", strvar.indexOf("%>")) > 0) {
-                                return true;
-                        }
-                }
-        }
-        return false;
-};
-
-function replace_Stats_In(strval, data, dataset, coldata) {
-        var resval = "";
-        var start = 0;
-        var prevstat = true;
-        while (strval.indexOf("#", start) >= 0) {
-                // strval.substring(start,)           ;
-                if (!prevstat) {
-                        var statOf = convertStat(strval.substring(start, strval.indexOf("#", start)), data, dataset, coldata);
-                        if (statOf.found) {
-                                resval = resval + statOf.resval;
-                                start = strval.indexOf("#", start) + 1;
-                                prevstat = true;
-                        } else {
-                                resval = resval + "#" + statOf.resval;
-                                start = strval.indexOf("#", start) + 1;
-                        }
-                } else {
-                        if (start > 0) resval = resval;
-                        resval = resval + strval.substring(start, strval.indexOf("#", start));
-                        start = strval.indexOf("#", start) + 1;
-                        prevstat = false;
-                }
-        }
-        if (!prevstat) resval = resval + "#";
-        resval = resval + strval.substring(start, strval.length);
-        return resval;
-};
-
-function convertStat(statval, data, dataset, coldata) {
-        var resval = statval;
-        var found = false;
-        if (typeof data.stats[statval.toLowerCase()] != "undefined" && typeof data.stats[statval.toLowerCase()] != "object") {
-                resval = data.stats[statval.toLowerCase()];
-                found = true;
-        } else if (statval.toLowerCase().substring(0, 3) == "ds_") {
-                stat = statval.toLowerCase().substring(3);
-                if (stat.indexOf("(") > 0) {
-                        var vdataset = stat.substring(stat.indexOf("(") + 1);
-                        vdataset = 1 * vdataset.substring(0, vdataset.indexOf(")"));
-                        var stat = stat.substring(0, stat.indexOf("("));
-                } else {
-                        vdataset = Math.max(1 * dataset, 0);
-                }
-                if (typeof data.datasets == "object") {
-                        if (typeof data.datasets[vdataset] == "object") {
-                                if (typeof data.datasets[vdataset].stats == "object") {
-                                        if (typeof data.datasets[vdataset].stats[stat] == "number") {
-                                                resval = data.datasets[vdataset].stats[stat];
-                                                found = true;
-                                        }
-                                }
-                        }
-                }
-        } else if (statval.toLowerCase().substring(0, 5) == "data_") {
-                stat = statval.toLowerCase().substring(5);
-                if (stat.indexOf("(") > 0) {
-                        vdataset = stat.substring(stat.indexOf("(") + 1);
-                        vdataset = 1 * vdataset.substring(0, vdataset.indexOf(")"));
-                        stat = stat.substring(0, stat.indexOf("("));
-                } else {
-                        vdataset = Math.max(1 * coldata, 0);
-                }
-                if (typeof data.datasets == "object") {
-                        if (typeof data.stats["data_" + stat] == "object") {
-                                if (typeof data.stats["data_" + stat][vdataset] == "number") {
-                                        resval = data.stats["data_" + stat][vdataset];
-                                        found = true;
-                                }
-                        }
-                }
-        }
-        return {
-                found: found,
-                resval: resval
-        };
-};