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fixed forecast report

This commit is contained in:
daniel 2018-09-12 10:34:14 +02:00
parent ed0d89ec73
commit 6312d2e38a
3 changed files with 56 additions and 84 deletions
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98
pandora_console/include/functions_forecast.php
View File

@ -20,31 +20,29 @@
*/
/**
* Create a prediction based on module data with least square method (linear regression)
* Create a prediction based on module data with least square method (linear regression)
*
* @param int Module id.
* @param int Period of the module data.
* @param int Period of the prediction or false to use it in prediction_date function (see below).
* @param int Period of the prediction or false to use it in prediction_date function (see below).
* @param int Maximun value using this function for prediction_date.
* @param int Minimun value using this function for prediction_date.
* @param bool Result data for CSV file exportation.
*
*
* @return array Void array or prediction of the module data.
*/
function forecast_projection_graph($module_id,
$period = SECONDS_2MONTHS, $prediction_period, $max_value = false,
$min_value = false, $csv = false) {
global $config;
$max_exec_time = ini_get('max_execution_time');
$max_exec_time = ini_get('max_execution_time');
if ($max_exec_time !== false) {
$max_exec_time = (int)$max_exec_time;
$max_exec_time = (int)$max_exec_time;
}
$begin_time = time();
$params =array(
@ -54,16 +52,16 @@ function forecast_projection_graph($module_id,
'projection' => true
);
$module_data = grafico_modulo_sparse ($params);
$module_data = grafico_modulo_sparse($params);
if (empty($module_data)) {
return array();
return array();
}
// Prevents bad behaviour over image error
// Prevents bad behaviour over image error
else if (!is_array($module_data) and preg_match('/^<img(.)*$/', $module_data)) {
return;
}
// Data initialization
$sum_obs = 0;
$sum_xi = 0;
@ -113,35 +111,16 @@ function forecast_projection_graph($module_id,
$cont++;
}
}
$cont--;
// Calculation over data above:
// 1. Calculation of linear correlation coefficient...
// 1.1 Average for X: Sum(Xi)/Obs
// 1.1 Average for X: Sum(Xi)/Obs
// 1.2 Average for Y: Sum(Yi)/Obs
// 2. Covariance between vars
// 3.1 Standard deviation for X: sqrt((Sum(Xi²)/Obs) - (avg X)²)
// 3.2 Standard deviation for Y: sqrt((Sum(Yi²)/Obs) - (avg Y)²)
// 3.1 Standard deviation for X: sqrt((Sum(Xi²)/Obs) - (avg X)²)
// 3.2 Standard deviation for Y: sqrt((Sum(Yi²)/Obs) - (avg Y)²)
// Linear correlation coefficient:
/*
if ($cont != 0) {
$covariance = $sum_xi_yi/$cont;
$dev_x = sqrt(($sum_xi2/$cont) - ($avg_x*$avg_x));
$dev_y = sqrt(($sum_yi2/$cont) - ($avg_y*$avg_y));
} else {
$covariance = 0;
$dev_x = 0;
$dev_y = 0;
}
// Prevents division by zero
if ($dev_x != 0 and $dev_y != 0) {
$linear_coef = $covariance / ($dev_x * $dev_y);
}
*/
// Agent interval could be zero, 300 is the predefined
if ($sum_obs == 0) {
$agent_interval = SECONDS_5MINUTES;
@ -149,37 +128,35 @@ function forecast_projection_graph($module_id,
else {
$agent_interval = $sum_diff_dates / $sum_obs;
}
// Could be a inverse correlation coefficient
// if $linear_coef < 0.0
// if $linear_coef >= -1.0 and $linear_coef <= -0.8999
// Function variables have an inverse linear relathionship!
// else
// Function variables don't have an inverse linear relathionship!
// else
// Function variables don't have an inverse linear relathionship!
// Could be a direct correlation coefficient
// else
// else
// if ($linear_coef >= 0.8999 and $linear_coef <= 1.0) {
// Function variables have a direct linear relathionship!
// else
// else
// Function variables don't have a direct linear relathionship!
// 2. Calculation of linear regresion...
$b_num = (($cont * $sum_xi_yi) - ($sum_xi * $sum_yi));
$b_den = (($cont * $sum_xi2) - ($sum_xi * $sum_xi));
if ($b_den == 0)
return;
$b = $b_num / $b_den;
$a_num = ($sum_yi) - ($b * $sum_xi);
if ($cont != 0) {
$a = $a_num / $cont;
} else {
$a = 0;
}
// Data inicialization
$output_data = array();
if ($prediction_period != false) {
@ -188,11 +165,11 @@ function forecast_projection_graph($module_id,
$current_ts = $last_timestamp;
$in_range = true;
$time_format_2 = '';
$temp_range = $period;
if ($period < $prediction_period)
$temp_range = $prediction_period;
if ($temp_range <= SECONDS_6HOURS) {
$time_format = 'H:i:s';
}
@ -206,15 +183,15 @@ function forecast_projection_graph($module_id,
elseif ($temp_range <= SECONDS_1MONTH) {
$time_format = 'M d';
$time_format_2 = 'H\h';
}
}
else {
$time_format = 'M d';
}
// Aplying linear regression to module data in order to do the prediction
$output_data = array();
// Aplying linear regression to module data in order to do the prediction
$idx = 0;
// Create data in graph format like
while ($in_range) {
$now = time();
@ -242,9 +219,10 @@ function forecast_projection_graph($module_id,
if ($current_ts - $last_timestamp >= 94608000) {
return false;
}
// Found it
if ($max_value >= $output_data[$idx][0] and $min_value <= $output_data[$idx][0]) {
if (($max_value >= $output_data[$idx][0]) &&
($min_value <= $output_data[$idx][0]) ) {
return $current_ts;
}
}
@ -254,7 +232,6 @@ function forecast_projection_graph($module_id,
$current_ts = $current_ts + $agent_interval;
$idx++;
}
return $output_data;
}
@ -264,8 +241,8 @@ function forecast_projection_graph($module_id,
* @param int Module id.
* @param int Given data period to make the prediction
* @param int Max value in the interval.
* @param int Min value in the interval.
*
* @param int Min value in the interval.
*
* @return mixed timestamp with the prediction date or false
*/
function forecast_prediction_date ($module_id,
@ -274,6 +251,5 @@ function forecast_prediction_date ($module_id,
if ($min_value > $max_value) {
return false;
}
return forecast_projection_graph($module_id, $period, false, $max_value, $min_value);
}

29
pandora_console/include/functions_graph.php
View File

@ -264,9 +264,7 @@ function grafico_modulo_sparse_data_chart (
$data_module_graph['id_module_type'] == 18 ||
$data_module_graph['id_module_type'] == 9 ||
$data_module_graph['id_module_type'] == 31 ||
$data_module_graph['id_module_type'] == 100 ||
$params['projection']
){
$data_module_graph['id_module_type'] == 100 ){
$data = db_get_all_rows_filter (
'tagente_datos',
@ -421,8 +419,7 @@ function grafico_modulo_sparse_data(
$data_module_graph['id_module_type'] == 18 ||
$data_module_graph['id_module_type'] == 9 ||
$data_module_graph['id_module_type'] == 31 ||
$data_module_graph['id_module_type'] == 100 ||
$params['projection'] ){
$data_module_graph['id_module_type'] == 100 ){
$array_data = grafico_modulo_sparse_data_chart (
$agent_module_id,
$date_array,
@ -924,7 +921,6 @@ function grafico_modulo_sparse ($params) {
$legend = array();
$array_events_alerts = array();
$date_array = array();
$date_array["period"] = $params['period'];
$date_array["final_date"] = $params['date'];
@ -1226,7 +1222,7 @@ function graphic_combined_module (
}
else{
$params['stacked'] = 'area';
$params['projection'] = $params_combined['projection'];
$params['projection'] = true;
}
if(!isset($params_combined['labels'])){
@ -1519,6 +1515,14 @@ function graphic_combined_module (
$date_array["final_date"] = $params['date'];
$date_array["start_date"] = $params['date'] - $params['period'];
if($params_combined['projection']){
$output_projection = forecast_projection_graph(
$module_list[0],
$params['period'],
$params_combined['projection']
);
}
$i=0;
$array_data = array();
foreach ($module_list as $key => $agent_module_id) {
@ -1585,10 +1589,13 @@ function graphic_combined_module (
$i++;
}
if($params_combined['projection'] && is_array($params_combined['projection'])){
$date_array_projection = max($params_combined['projection']);
$date_array['final_date'] = $date_array_projection[0] / 1000;
$array_data['projection']['data']= $params_combined['projection'];
if($params_combined['projection']){
// If projection doesn't have data then don't draw graph
if ($output_projection != NULL) {
$date_array_projection = max($output_projection);
$date_array['final_date'] = $date_array_projection[0] / 1000;
$array_data['projection']['data']= $output_projection;
}
}
//summatory and average series

13
pandora_console/include/functions_reporting.php
View File

@ -3557,17 +3557,6 @@ function reporting_projection_graph($report, $content,
switch ($type) {
case 'dinamic':
case 'static':
$output_projection = forecast_projection_graph(
$content['id_agent_module'],
$content['period'],
$content['top_n_value']
);
// If projection doesn't have data then don't draw graph
if ($output_projection == NULL) {
$output_projection = false;
}
$params =array(
'period' => $content['period'],
'width' => $width,
@ -3581,7 +3570,7 @@ function reporting_projection_graph($report, $content,
);
$params_combined = array(
'projection' => $output_projection
'projection' => $content['top_n_value'],
);
$return['chart'] = graphic_combined_module(