Files
cacti/lib/graph_variables.php
TheWitnessandTheWitness 3ab4c69fb7 PHPStan Level 8 - Phase 1 Conversion (#8135)
* PHPStan Level 8 - Phase 1 Conversion

Reduces the real (no-baseline) PHPStan level 8 error count from ~2,724 to 425
and regenerates phpstan-baseline.neon accordingly (8,941 -> 1,921 lines).

Core type-safety changes
- lib/database.php: narrow db_fetch_row()/db_fetch_row_prepared() to return
  array (was bool|array) and db_fetch_assoc()/db_fetch_assoc_prepared() to
  return array (was mixed); the _prepared workers coerce the connection-failure
  path to an empty array so the declared type is honest. empty()/cacti_sizeof()
  checks are unaffected.
- lib/database.php: narrow $db_conn guards from is_object() to instanceof PDO in
  the transaction/quote/insert-id helpers so the PDO calls resolve.
- lib/mib_cache.php: the fluent MibCache methods mib()/object()/table()/row()
  now return self instead of a bare object so chained calls type-check.

Type-safety casts and guards (mechanical, behaviour-preserving)
- Cast string|false/|null builtin results feeding string parameters
  (json_decode, base64_encode, trim, htmle, preg_replace, explode, etc.).
- Cast int|string / int|false values feeding int id/pid parameters.
- Guard resource|false fopen()/popen() handles before fwrite/fclose/fread, and
  wrap foreach over array|false/list|false results with `?: []`.

Genuine bugs found and fixed
- cli/add_tree.php / lib/api_tree.php: site tree nodes could not be created via
  the CLI - the --site-id option was never parsed, $nodeTypes had no 'site'
  entry (passing null to api_tree_item_save(int $type) -> TypeError), and
  api_tree_item_save() never persisted site_id. All three fixed.
- tree.php: leaves_exist() is typed : int but returned db_fetch_assoc_prepared()
  (an array of rows) for a SELECT COUNT(*); now uses db_fetch_cell_prepared()
  and returns the scalar count.
- lib/mib_cache.php: $entries_per_object was a float (division / ceil) used as
  an array key (PHP 8.1 implicit float-to-int key deprecation); now cast to int.

Config
- .phpstan.neon: add notIdentical.alwaysTrue and booleanAnd.alwaysFalse to the
  existing always-true/false ignore family (same "PHPStan gets confused"
  dynamic-constant cause already covered by identical.alwaysTrue,
  notEqual.alwaysTrue, booleanAnd.leftAlwaysTrue, etc.).
- phpstan-baseline.neon: regenerated; the remaining 425 entries are the
  untouched long tail for Phase 2.

* Remove redundant @phpstan-ignore comments

Follow-up cleanup for the level 8 Phase 1 work. Removes 14 inline
@phpstan-ignore comments that no longer suppress any reported error:

- cli/repair_database.php: `@phpstan-ignore booleanAnd.alwaysFalse` is now
  covered by the global booleanAnd.alwaysFalse ignore added to .phpstan.neon.
- 13 others (host.php, include/global.php, include/session.php,
  lib/api_automation.php x2, lib/functions.php x2, lib/html_utility.php x2,
  lib/installer.php, lib/package.php, lib/reports.php, lib/rrd.php) no longer
  match any reported error after the type-safety fixes (e.g. the
  db_fetch_row_prepared() return-type narrowing removed the offset-assign
  errors the api_automation ignores were suppressing).

Verified with reportUnmatchedIgnoredErrors enabled: 0 unmatched ignores
remain and the full level 8 run still reports 0 errors.

* ci: satisfy validator ratchet and refresh security sink baselines

- lib/api_tree.php: give the new tree-item site_id a real numeric
  constraint ('^[-0-9]+$', matching html_reports.php) instead of an
  empty regex, so the validator constraint ratchet passes without
  bumping its baseline.
- tests/security/baselines: refresh the three sink/hotspot signatures
  whose code text changed from the (string) casts added in this branch
  (lib/poller.php setsid, cli/rrdresize.php json_encode, lib/import.php
  simplexml_load_string).

* ci(js): allow DOMPurify 3.4.16 and update sync_js pin test

The dependabot bump (#8134) moved package.json/package-lock.json to
DOMPurify 3.4.16 on develop but left tests/js/sync_js.test.mjs pinned to
3.4.15, so the PR merge commit fails the 'DOMPurify is pinned' contract.
Bring package.json/package-lock.json to 3.4.16 (matching develop) and
update the pin test to expect 3.4.16.

* test: update sql.php null-handling assertion for the (string) cast

This branch changed scripts/sql.php from trim(\ ?? '') to
trim((string) \) (the phpstan-safe form that coerces both null and
false from shell_exec()). Update SqlScriptsTest's null-return assertion
to match the new cast instead of the removed '?? ''.

* fix: address Copilot review - ownership IDs, fopen guards, mib_cache bound

- chown()/chgrp(): pass integer UID/GID from fileowner()/filegroup()
  (guarding the false lookup) instead of string-casting them, which made
  them resolve account/group names like '1001' and fail. Covers
  lib/api_device.php, lib/boost.php and poller_maintenance.php (x2).
- fopen() failure now short-circuits instead of reporting success:
  lib/package.php returns false, lib/clog_webapi.php and utilities.php
  render an error, and snmpagent_mibcachechild.php skips the cache write
  and sentinel unlink so a concurrent writer's lock is preserved.
- lib/mib_cache.php: keep the float quotient as the loop bound and cast
  only the array offset, so a non-even entries/columns split no longer
  truncates the loop and drops a cached row.

* revert: keep db_fetch_* returning false on error; baseline Level 8 instead

Per review, restoring the intentional fail-safe: db_fetch_row[_prepared]()
return bool|array and db_fetch_assoc[_prepared]() return mixed again, so a
genuine SQL error (not just a missing connection) is signalled as false and
the === false checks in cdef_is_in_use(), boost_process_* and aggregate.php
work as before. Dropped the is_array() ? : [] coercion.

Level 8 stays green by regenerating phpstan-baseline.neon to capture the
re-introduced bool|array/mixed call-site errors (the ~1,850 the narrowing
had eliminated). Tightening those callers to drop them from the baseline is
Phase 2 work.

---------

Co-authored-by: TheWitness <copilot@users.noreply.github.com>
2026-10-02 10:08:56 -04:00

814 lines
28 KiB
PHP

<?php
/*
+-------------------------------------------------------------------------+
| Copyright (C) 2004-2026 The Cacti Group |
| |
| This program is free software; you can redistribute it and/or |
| modify it under the terms of the GNU General Public License |
| as published by the Free Software Foundation; either version 2 |
| of the License, or (at your option) any later version. |
| |
| This program is distributed in the hope that it will be useful, |
| but WITHOUT ANY WARRANTY; without even the implied warranty of |
| MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
| GNU General Public License for more details. |
+-------------------------------------------------------------------------+
| Cacti: The Complete RRDtool-based Graphing Solution |
+-------------------------------------------------------------------------+
| This code is designed, written, and maintained by the Cacti Group. See |
| about.php and/or the AUTHORS file for specific developer information. |
+-------------------------------------------------------------------------+
| http://www.cacti.net/ |
+-------------------------------------------------------------------------+
*/
/**
* nth_percentile - given a data source, calculate the Nth percentile for a given over a time period
*
* @param mixed $local_data_ids The data source array to perform the Nth percentile calculation
* @param int $start_seconds Start seconds of time range
* @param int $end_seconds Stop seconds of time range
* @param int $percentile Nth Percentile to calculate, integer between 1 and 99
* @param int $resolution The accuracy of the data measured in seconds
* @param bool $peak Include the peak values in the stats array
*
* @return mixed Returns a string, int or float containing the requested percentile
*/
function nth_percentile(mixed $local_data_ids, int $start_seconds, int $end_seconds, int $percentile = 95,
int $resolution = 0, bool $peak = false) : mixed {
$stats = json_decode(rrdtool_function_stats($local_data_ids, $start_seconds, $end_seconds, $percentile, $resolution, $peak), true);
if ($peak) {
/* rrdtool_function_stats() emits an empty peak when the RRDfile
* lacks a MAX consolidation function, so treat it as absent and
* fall back to the AVERAGE based statistics */
if (array_key_exists('peak', $stats) && cacti_sizeof($stats['peak'])) {
return $stats['peak'];
}
if (array_key_exists('avg', $stats)) {
return $stats['avg'];
} else {
return $stats;
}
} else {
if (array_key_exists('avg', $stats)) {
return $stats['avg'];
}
if (array_key_exists('peak', $stats)) {
return $stats['peak'];
} else {
return $stats;
}
}
}
/**
* rrdtool_function_stats - given a data source, calculate a number of statistics for an RRDfile or files
* over a specified time period
*
* @param mixed $local_data_ids The data source array to perform the Nth percentile calculation
* @param int $start_seconds Start seconds of time range
* @param int $end_seconds Stop seconds of time range
* @param int $percentile Nth Percentile to calculate, integer between 1 and 99
* @param int $resolution The accuracy of the data measured in seconds
* @param bool $peak Include peak values in stats
* @param mixed $rrdtool_pipe The RRDtool socket connection if there is one
*
* @return string JSON data containing each data source item, and its 95th percentile
*/
function rrdtool_function_stats(mixed $local_data_ids, int $start_seconds, int $end_seconds, int $percentile = 95, int $resolution = 0,
bool $peak = false, mixed $rrdtool_pipe = null) : string {
include_once(CACTI_PATH_LIBRARY . '/rrd.php');
if (!is_array($local_data_ids)) {
return (string) json_encode([]);
}
// initialize some variables
$sum_array = [];
$fetch_array_avg = [];
$fetch_array_max = [];
$good_data = false;
/* Do a fetch for each data source and discard
* nth_percentile_maximum and any invalid data sources
*
* After this loop is finished, all data will have
* been retrieved from the RRDfiles.
*/
foreach ($local_data_ids as $ldi => $data_source_name) {
global $user_time, $system_time, $real_time;
global $total_user, $total_system, $total_real;
// more error checking for invalid data
if ($ldi == 0) {
continue;
}
if (empty($total_user)) {
$total_user = 0.0;
}
if (empty($total_system)) {
$total_system = 0.0;
}
if (empty($total_real)) {
$total_real = 0.0;
}
// See if the RRDfile contains the MAX consolidation function, if so prime the array with the fetch data
if ($peak) {
if (rrdtool_function_contains_cf($ldi, 'MAX', $rrdtool_pipe)) {
$total_user += $user_time;
$total_system += $system_time;
$total_real += $real_time;
$fetch_array_max[$ldi] = rrdtool_function_fetch($ldi, $start_seconds, $end_seconds, $resolution, false, '', 'MAX', $rrdtool_pipe);
$total_user += $user_time;
$total_system += $system_time;
$total_real += $real_time;
}
}
// See if the RRDfile contains the AVERAGE consolidation function, if so prime the array with the fetch data
if (rrdtool_function_contains_cf($ldi, 'AVERAGE', $rrdtool_pipe)) {
$total_user += $user_time;
$total_system += $system_time;
$total_real += $real_time;
$fetch_array_avg[$ldi] = rrdtool_function_fetch($ldi, $start_seconds, $end_seconds, $resolution, false, '', 'AVERAGE', $rrdtool_pipe);
$total_user += $user_time;
$total_system += $system_time;
$total_real += $real_time;
}
// clean up unwanted data source items from the AVERAGE cf data
if (isset($fetch_array_avg[$ldi]) && cacti_sizeof($fetch_array_avg[$ldi])) {
if (isset($fetch_array_avg[$ldi]['data_source_names'])) {
$good_data = true;
} else {
unset($fetch_array_avg[$ldi]);
continue;
}
// discard the unused data sources, we will figure it out ourselves
foreach ($fetch_array_avg[$ldi]['data_source_names'] as $index => $name) {
// clean up DS items that aren't defined on the graph
if (!in_array($name, $local_data_ids[$ldi], true)) {
if (isset($fetch_array_avg[$ldi]['data_source_names'][$index])) {
unset($fetch_array_avg[$ldi]['data_source_names'][$index]);
}
if (isset($fetch_array_avg[$ldi]['values'][$index])) {
unset($fetch_array_avg[$ldi]['values'][$index]);
}
}
}
}
// clean up unwanted data source items from the MAX cf data
if (isset($fetch_array_max[$ldi]) && cacti_sizeof($fetch_array_max[$ldi])) {
if (isset($fetch_array_max[$ldi]['data_source_names'])) {
$good_data = true;
} else {
unset($fetch_array_max[$ldi]);
continue;
}
// discard the unused data sources, we will figure it out ourselves
foreach ($fetch_array_max[$ldi]['data_source_names'] as $index => $name) {
// clean up DS items that aren't defined on the graph
if (!in_array($name, $local_data_ids[$ldi], true)) {
if (isset($fetch_array_max[$ldi]['data_source_names'][$index])) {
unset($fetch_array_max[$ldi]['data_source_names'][$index]);
}
if (isset($fetch_array_max[$ldi]['values'][$index])) {
unset($fetch_array_max[$ldi]['values'][$index]);
}
}
}
}
}
/* Do a sanity check, return right away if we don't have
* good data. Else prepare a new array with summary data.
*/
if (!$good_data) {
return (string) json_encode([]);
}
$stats = [];
if (cacti_sizeof($fetch_array_avg)) {
$stats['avg'] = nth_percentile_fetch_statistics($percentile, $local_data_ids, $fetch_array_avg, 'AVERAGE');
}
if ($peak && cacti_sizeof($fetch_array_max)) {
$stats['peak'] = nth_percentile_fetch_statistics($percentile, $local_data_ids, $fetch_array_max, 'MAX');
} else {
$stats['peak'] = [];
}
return (string) json_encode($stats);
}
function nth_percentile_fetch_statistics(int $percentile, array &$local_data_ids, array &$fetch_array, string $cf) : array {
// start by summing the data across local data ids, for the average cf
$asum_array = [];
foreach ($local_data_ids as $ldi => $data_source_name) {
if (cacti_sizeof($fetch_array[$ldi]['data_source_names'])) {
foreach ($fetch_array[$ldi]['data_source_names'] as $index => $ds_name) {
if (isset($fetch_array[$ldi]['values'][$index]) && cacti_sizeof($fetch_array[$ldi]['values'][$index])) {
foreach ($fetch_array[$ldi]['values'][$index] as $timestamp => $data) {
// rrdtool emits 'U'/NaN for gaps; skip them so they do not poison the sum
if (!is_numeric($data) || !is_finite((float) $data)) {
continue;
}
if (isset($asum_array[$ds_name]) && isset($asum_array[$ds_name][$timestamp])) {
$asum_array[$ds_name][$timestamp] += $data;
} else {
$asum_array[$ds_name][$timestamp] = $data;
}
}
}
}
}
}
// print '<pre>';print_r($asum_array);print '</pre>';
// next get the max values of all the data sources
$max_values_array = [];
if (cacti_sizeof($asum_array)) {
foreach ($asum_array as $sum_by_timestamp) {
foreach ($sum_by_timestamp as $timestamp => $data) {
if (!isset($max_values_array[$timestamp])) {
$max_values_array[$timestamp] = $data;
} else {
$max_values_array[$timestamp] = max($data, $max_values_array[$timestamp]);
}
}
}
}
// store some known information for legacy cacti behavior
$asum_array['nth_percentile_maximum'] = $max_values_array;
// get the sum data now across all data sources
$sum_values_array = [];
if (cacti_sizeof($asum_array)) {
foreach ($asum_array as $ds_name => $sum_by_timestamp) {
if ($ds_name == 'nth_percentile_maximum') {
continue;
}
foreach ($sum_by_timestamp as $timestamp => $data) {
if (!isset($sum_values_array[$timestamp])) {
$sum_values_array[$timestamp] = $data;
} else {
$sum_values_array[$timestamp] += $data;
}
}
}
}
// store some known information for legacy cacti behavior
$asum_array['nth_percentile_sum'] = $sum_values_array;
// get some nice analytical statistics about the data
$stats = [];
$agg_total = 0;
foreach ($asum_array as $ds_name => $data_by_timestamp) {
$cstats['stats_' . $ds_name] = cacti_stats_calc($data_by_timestamp, $percentile);
$stats[$ds_name] = $cstats['stats_' . $ds_name]['p' . $percentile . 'n'];
// scan all non built-in data sources for aggregate total data
if ($ds_name != 'nth_percentile_sum' &&
$ds_name != 'nth_percentile_maximum') {
if ($agg_total < $cstats['stats_' . $ds_name]['p' . $percentile . 'n']) {
$agg_total = $cstats['stats_' . $ds_name]['p' . $percentile . 'n'];
}
}
}
// store some known information for legacy cacti behavior
$stats['nth_percentile_aggregate_total'] = $agg_total;
$stats += $cstats;
return $stats;
}
function cacti_percentile_index(int $elements, int $percentile) : int {
if ($elements <= 0 || $percentile <= 0 || $percentile >= 100) {
return 0;
}
// Values are sorted descending. rrdtool's VDEF PERCENT selects the ascending
// rank round(percentile/100 * N), so the matching zero-based descending index
// is N - round(percentile/100 * N). PHP round() is half-away-from-zero, which
// matches rrdtool's C round() on the .5 ties. Verified against rrdtool for
// 28/29/30/31-day months (N = 8064/8352/8640/8928).
$index = $elements - (int) round($elements * $percentile / 100);
return max(0, min($elements - 1, $index));
}
function cacti_stats_calc(array $array, int $ptile = 95) : array {
rsort($array, SORT_NUMERIC);
$elements = cacti_sizeof($array);
if ($elements == 0) {
$results = [
'p95n' => 0,
'p90n' => 0,
'p75n' => 0,
'p50n' => 0,
'p25n' => 0,
'average' => 0,
'peak' => 0,
'sum' => 0,
'elements' => 0,
'variance' => 0,
'stddev' => 0
];
$results['p' . $ptile . 'n'] = 0;
return $results;
}
$rsquared = 0;
$sum = array_sum($array);
$peak = max($array);
$average = $sum / $elements;
$var = 'p' . $ptile . 'n';
if ($var == 'p95n') {
$var = '';
}
foreach ($array as $number) {
$rsquared += ($number - $average) ** 2;
}
$variance = $rsquared / $elements;
$ptile_index = cacti_percentile_index($elements, $ptile);
$p95n_index = cacti_percentile_index($elements, 95);
$p90n_index = cacti_percentile_index($elements, 90);
$p75n_index = cacti_percentile_index($elements, 75);
$p50n_index = cacti_percentile_index($elements, 50);
$p25n_index = cacti_percentile_index($elements, 25);
$results = [
'p95n' => $array[$p95n_index] ?? 0,
'p90n' => $array[$p90n_index] ?? 0,
'p75n' => $array[$p75n_index] ?? 0,
'p50n' => $array[$p50n_index] ?? 0,
'p25n' => $array[$p25n_index] ?? 0,
'average' => $average,
'peak' => $peak,
'sum' => $sum,
'elements' => $elements,
'variance' => $variance,
'stddev' => sqrt($rsquared / $elements)
];
if ($var != '') {
$results[$var] = $array[$ptile_index] ?? 0;
}
return $results;
}
/**
* bandwidth_summation - given a data source, sums all data in the rrd for a given
* time period
*
* @param int $local_data_id The data source to perform the summation for
* @param int $start_time The start time to use for the data calculation. this value can
* either be absolute (unix timestamp) or relative (to now)
* @param int $end_time The end time to use for the data calculation. this value can
* either be absolute (unix timestamp) or relative (to now)
* @param int $rra_steps The accuracy of the data measured in seconds
* @param int $ds_steps How many periods each sample in the RRA counts for, values above '1'
* result in an averaged summation
*
* @return array An array containing each data source item, and its sum
*/
function bandwidth_summation(int $local_data_id, int $start_time, int $end_time, int $rra_steps, int $ds_steps) : array {
$fetch_array = @rrdtool_function_fetch($local_data_id, $start_time, $end_time, $rra_steps * $ds_steps);
$return_array = [];
if (!isset($fetch_array['data_source_names']) || cacti_count($fetch_array['data_source_names']) == 0) {
return $return_array;
}
// loop through each regexp determined above (or each data source)
for ($i = 0; $i < cacti_count($fetch_array['data_source_names']); $i++) {
if (isset($fetch_array['values'][$i])) {
$sum = array_sum($fetch_array['values'][$i]);
if (cacti_count($fetch_array['values'][$i]) > 0) {
$requested_step = $ds_steps * $rra_steps;
$effective_step = $fetch_array['timestamp']['step'] ?? 0;
$sum *= $effective_step > 0 ? $effective_step : $requested_step;
} else {
$sum = 0;
}
// collect summation values in this array so we can return them
$return_array[$fetch_array['data_source_names'][$i]] = $sum;
}
}
return $return_array;
}
function is_graphable_item(string $item) : bool {
if (preg_match('/(AREA|STACK|LINE[123])/', $item)) {
return true;
} else {
return false;
}
}
/**
* variable_nth_percentile - given a Nth percentile variable, calculate the Nth percentile
* and format it for display on the graph
*
* @param array $regexp_match_array The array that contains each argument in the Nth percentile variable. it
* should be formatted like so:
* $arr[0] // full variable string
* $arr[1] // Nth percentile
* $arr[2] // bits or bytes
* $arr[3] // power of 10 divisor
* $arr[4] // current, total, max, total_peak, all_max_current, all_max_peak
* $arr[5] // digits of floating point precision
* @param array $graph An array that contains the current graph data
* @param array $graph_item An array that contains the current graph item
* @param array $graph_items An array that contains all graph items
* @param int $graph_start The start time to use for the data calculation. this value can
* either be absolute (unix timestamp) or relative (to now)
* @param int $graph_end The end time to use for the data calculation. this value can
* either be absolute (unix timestamp) or relative (to now)
* @param int $resolution Effective RRA resolution selected for the graph
*
* @return string - a string containing the Nth percentile suitable for placing on the graph
*/
function variable_nth_percentile(array &$regexp_match_array, array &$graph, array &$graph_item, array &$graph_items,
int $graph_start, int $graph_end, int $resolution = 0) : string {
global $graph_item_types;
$nth_cache = [];
$local_data_array = [];
if (cacti_sizeof($regexp_match_array) == 0) {
return '0';
}
if ($graph['base_value'] == 1024) {
/* the divisor must be 1024^(power/3), the binary analogue of
10^power; dividing by 10.24^power printed values about
1.024^(2*power/3) too low (#7211) */
$base = 2;
$exp_scale = 10 / 3;
} else {
$base = 10;
$exp_scale = 1;
}
// Convert the regex matches to human readable
// Unexploded format is |95:bits:6:max:2|
$percentile = $regexp_match_array[1];
$bytebit = $regexp_match_array[2];
$power = $regexp_match_array[3];
$type = $regexp_match_array[4];
// determine the floating point precision
if (is_numeric($regexp_match_array[5])) {
$round_to = $regexp_match_array[5];
} else {
$round_to = 2;
}
// error Nth Percentile variable is incorrect
if ($percentile < 1 || $percentile > 99) {
return '-1';
}
if (empty($graph_item['local_data_id'])) {
$graph_item['local_data_id'] = 0;
}
$gi = [];
if (cacti_sizeof($graph_items)) {
foreach ($graph_items as $item) {
if ($item['local_data_id'] > 0 && $item['data_source_name'] != '') {
if (!empty($item['data_template_rrd_id']) &&
!empty($item['local_data_id']) &&
is_graphable_item($graph_item_types[$item['graph_type_id']])) {
$gi[$item['data_source_name'] . '|||' . $item['local_data_id']] = true;
}
}
}
foreach ($gi as $data_source => $true) {
[$data_source_name, $local_data_id] = explode('|||', $data_source);
$local_data_array[$local_data_id][] = $data_source_name;
}
}
// Get the Nth percentile values
if (!cacti_sizeof($nth_cache)) {
switch ($type) {
case 'current':
// Query data for the individual case
$local_data_array = array_intersect_key($local_data_array, array_flip([$graph_item['local_data_id']]));
$nth_cache = nth_percentile($local_data_array, $graph_start, $graph_end, $percentile, $resolution);
break;
case 'max':
// Query data for the individual case
$local_data_array = array_intersect_key($local_data_array, array_flip([$graph_item['local_data_id']]));
$nth_cache = nth_percentile($local_data_array, $graph_start, $graph_end, $percentile, $resolution, true);
break;
case 'total':
case 'all_max_current':
if (cacti_sizeof($local_data_array)) {
$nth_cache = nth_percentile($local_data_array, $graph_start, $graph_end, $percentile, $resolution);
}
break;
case 'total_peak':
case 'all_max_peak':
if (cacti_sizeof($local_data_array)) {
$nth_cache = nth_percentile($local_data_array, $graph_start, $graph_end, $percentile, $resolution, true);
}
break;
case 'aggregate':
case 'aggregate_sum':
if (cacti_sizeof($local_data_array)) {
$nth_cache = nth_percentile($local_data_array, $graph_start, $graph_end, $percentile, $resolution);
}
break;
case 'aggregate_peak':
case 'aggregate_max':
case 'aggregate_sum_peak':
if (cacti_sizeof($local_data_array)) {
$nth_cache = nth_percentile($local_data_array, $graph_start, $graph_end, $percentile, $resolution, true);
}
break;
case 'aggregate_current':
case 'aggregate_current_peak':
$local_data_array = [];
if ($graph_item['data_source_name'] != '') {
foreach ($graph_items as $graph_element) {
if ($graph_item['data_source_name'] == $graph_element['data_source_name'] &&
!empty($graph_element['data_template_rrd_id']) &&
!empty($graph_element['local_data_id']) &&
is_graphable_item($graph_item_types[$graph_element['graph_type_id']])) {
$local_data_array[$graph_element['local_data_id']][] = $graph_element['data_source_name'];
}
}
if ($type == 'aggregate_current') {
if (cacti_sizeof($local_data_array)) {
$nth_cache = nth_percentile($local_data_array, $graph_start, $graph_end, $percentile, $resolution);
}
} else {
if (cacti_sizeof($local_data_array)) {
$nth_cache = nth_percentile($local_data_array, $graph_start, $graph_end, $percentile, $resolution, true);
}
}
}
break;
}
}
$nth = 0;
// format the output according to args passed to the variable
switch($type) {
case 'current': // Total of current data source from AVERAGE or MAX consolidation function
if (!empty($nth_cache[$graph_item['data_source_name']])) {
$nth = $nth_cache[$graph_item['data_source_name']];
$nth = ($bytebit == 'bits') ? $nth * 8 : $nth;
$nth /= $base ** ($power * $exp_scale);
}
break;
case 'total': // Total of the current data source name
case 'total_peak':
case 'aggregate_sum':
case 'aggregate_sum_peak':
if (!empty($nth_cache['nth_percentile_sum'])) {
$nth = $nth_cache['nth_percentile_sum'];
$nth = ($bytebit == 'bits') ? $nth * 8 : $nth;
$nth /= $base ** ($power * $exp_scale);
}
break;
case 'all_max_current': // Max of all data sources
case 'all_max_peak':
case 'aggregate_max':
case 'aggregate_peak':
case 'aggregate_current_peak':
case 'max':
if (!empty($nth_cache['nth_percentile_maximum'])) {
$nth = $nth_cache['nth_percentile_maximum'];
$nth = ($bytebit == 'bits') ? $nth * 8 : $nth;
$nth /= $base ** ($power * $exp_scale);
}
break;
case 'aggregate':
case 'aggregate_current':
if (!empty($nth_cache['nth_percentile_aggregate_total'])) {
$nth = $nth_cache['nth_percentile_aggregate_total'];
$nth = ($bytebit == 'bits') ? $nth * 8 : $nth;
$nth /= $base ** ($power * $exp_scale);
}
break;
}
return sprintf('%s', round($nth, $round_to));
}
/**
* variable_bandwidth_summation - given a bandwidth summation variable, calculate the summation
* and format it for display on the graph
*
* @param array $regexp_match_array The array that contains each argument in the bandwidth summation variable. it
* should be formatted like so:
* $arr[0] // full variable string
* $arr[1] // power of 10 divisor or 'auto'
* $arr[2] // current, total
* $arr[3] // digits of floating point precision
* $arr[4] // seconds to perform the calculation for or 'auto'
* @param array $graph An array that contains the current graph data
* @param array $graph_item An array that contains the current graph item
* @param array $graph_items An array that contains all graph items
* @param int $graph_start The start time to use for the data calculation. this value can
* either be absolute (unix timestamp) or relative (to now)
* @param int $graph_end The end time to use for the data calculation. this value can
* either be absolute (unix timestamp) or relative (to now)
* @param int $rra_step How many periods each sample in the RRA counts for, values
* above '1' result in an averaged summation
* @param int $ds_step How many seconds each period represents
*
* @return string A string containing the bandwidth summation suitable for placing on the graph
*/
function variable_bandwidth_summation(array &$regexp_match_array, array &$graph, array &$graph_item, array &$graph_items,
int $graph_start, int $graph_end, int $rra_step, int $ds_step) : string {
global $graph_item_types;
if (cacti_sizeof($regexp_match_array) == 0) {
return '0';
}
if (empty($graph_item['local_data_id'])) {
$graph_item['local_data_id'] = 0;
$regexp_match_array[2] = 'total';
}
if ($graph['base_value'] == 1024) {
/* the divisor must be 1024^(power/3), the binary analogue of
10^power; the auto path below already uses true powers of 1024 */
$base = 2;
$exp_scale = 10 / 3;
} else {
$base = 10;
$exp_scale = 1;
}
if (is_numeric($regexp_match_array[4])) {
$summation_timespan_start = -$regexp_match_array[4];
} else {
$summation_timespan_start = $graph_start;
}
$summation_cache = [];
switch($regexp_match_array[2]) {
case 'current':
$summation_cache[$graph_item['local_data_id']] = bandwidth_summation($graph_item['local_data_id'], (int) $summation_timespan_start, $graph_end, $rra_step, $ds_step);
break;
case 'total':
foreach ($graph_items as $graph_element) {
if (!empty($graph_element['data_template_rrd_id']) &&
!empty($graph_element['local_data_id']) &&
is_graphable_item($graph_item_types[$graph_element['graph_type_id']])) {
$summation_cache[$graph_element['local_data_id']] = bandwidth_summation($graph_element['local_data_id'], (int) $summation_timespan_start, $graph_end, $rra_step, $ds_step);
}
}
break;
case 'atomic':
$summation_cache[$graph_item['local_data_id']] = bandwidth_summation($graph_item['local_data_id'], (int) $summation_timespan_start, $graph_end, $rra_step, 1);
break;
}
$summation = 0;
// format the output according to args passed to the variable
switch ($regexp_match_array[2]) {
case 'current':
case 'atomic':
if (isset($summation_cache[$graph_item['local_data_id']][$graph_item['data_source_name']])) {
$summation = $summation_cache[$graph_item['local_data_id']][$graph_item['data_source_name']];
}
break;
case 'total':
foreach ($graph_items as $graph_element) {
if (!empty($graph_element['data_template_rrd_id']) &&
!empty($graph_element['local_data_id']) &&
isset($summation_cache[$graph_element['local_data_id']][$graph_element['data_source_name']]) &&
is_graphable_item($graph_item_types[$graph_element['graph_type_id']])) {
$summation += $summation_cache[$graph_element['local_data_id']][$graph_element['data_source_name']];
}
}
break;
}
if (preg_match('/\d+/', $regexp_match_array[1])) {
$summation /= $base ** ($regexp_match_array[1] * $exp_scale);
} elseif ($regexp_match_array[1] == 'auto') {
if ($graph['base_value'] == 1000) {
if ($summation < 1000) {
$summation_label = 'B';
} elseif ($summation < 1000000) {
$summation_label = 'KB';
$summation /= 1000;
} elseif ($summation < 1000000000) {
$summation_label = 'MB';
$summation /= 1000000;
} elseif ($summation < 1000000000000) {
$summation_label = 'GB';
$summation /= 1000000000;
} else {
$summation_label = 'TB';
$summation /= 1000000000000;
}
} else {
if ($summation < 1024) {
$summation_label = 'iB';
} elseif ($summation < 1048576) {
$summation_label = 'KiB';
$summation /= 1024;
} elseif ($summation < 1073741824) {
$summation_label = 'MiB';
$summation /= 1048576;
} elseif ($summation < 1099511627776) {
$summation_label = 'GiB';
$summation /= 1073741824;
} else {
$summation_label = 'TiB';
$summation /= 1099511627776;
}
}
}
// determine the floating point precision
if (is_numeric($regexp_match_array[3])) {
$round_to = $regexp_match_array[3];
} else {
$round_to = 2;
}
// substitute in the final result and round off to two decimal digits
if (isset($summation_label)) {
return sprintf('%10s', number_format_i18n($summation, $round_to) . " $summation_label");
} else {
return sprintf('%10s', number_format_i18n($summation, $round_to));
}
}