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mirror of https://github.com/beestat/app.git synced 2025-05-24 02:14:03 -04:00
beestat/api/temperature_profile.php
2019-10-16 20:46:41 -04:00

756 lines
27 KiB
PHP

<?php
/**
* Some functionality for generating and working with temperature profiles.
* Per ecobee documentation: The values supplied for any given 5-minute
* interval is the value at the start of the interval and is not an average.
*
* @author Jon Ziebell
*/
class temperature_profile extends cora\api {
public static $exposed = [
'private' => [],
'public' => []
];
public static $cache = [
'generate' => 604800 // 7 Days
];
/**
* Generate a temperature profile for the specified thermostat.
*
* @param int $thermostat_id
*
* @return array
*/
public function generate($thermostat_id) {
set_time_limit(0);
// Make sure the thermostat_id provided is one of yours since there's no
// user_id security on the runtime_thermostat table.
$thermostats = $this->api('thermostat', 'read_id');
if (isset($thermostats[$thermostat_id]) === false) {
throw new Exception('Invalid thermostat_id.', 10300);
}
/**
* This is an interesting thing to fiddle with. Basically, the longer the
* minimum sample duration, the better your score. For example, let's say
* I set this to 10m and my 30° delta is -1°. If I increase the time to
* 60m, I may find that my 30° delta decreases to -0.5°.
*
* Initially I thought something was wrong, but this makes logical sense.
* If I'm only utilizing datasets where the system was completely off for
* a longer period of time, then I can infer that the outdoor conditions
* were favorable to allowing that to happen. Higher minimums most likely
* only include sunny periods with low wind.
*
* For now this is set to 30m, which I feel is an appropriate requirement.
* I am not factoring in any variables outside of temperature for now.
* Note that 30m is a MINIMUM due to the event_runtime_thermostat_text_id logic that
* will go back in time by 30m to account for sensor changes if the
* calendar event changes.
*/
$minimum_sample_duration = [
'heat' => 300,
'cool' => 300,
'resist' => 1800
];
/**
* How long the system must be on/off for before starting a sample. Setting
* this to 5 minutes will use the very first sample which is fine if you
* assume the temperature in the sample is taken at the end of the 5m.
*/
$minimum_off_for = 300;
$minimum_on_for = 300;
/**
* Increasing this value will decrease the number of data points by
* allowing for larger outdoor temperature swings in a single sample. For
* example, a value of 1 will start a new sample if the temperature
* changes by 1°, and a value of 5 will start a new sample if the
* temperature changes by 5°.
*/
$smoothing = 1;
/**
* Require this many individual samples in a delta for a specific outdoor
* temperature. Increasing this basically cuts off the extremes where
* there are fewer samples.
*/
$required_samples = 2;
/**
* Require this many individual points before a valid temperature profile
* can be returned.
*/
$required_points = 5;
/**
* How far back to query for additional data. For example, when the
* event_runtime_thermostat_text_id changes I pull data from 30m ago. If that data is
* not available in the current runtime chunk, then it will fail. This
* will make sure that data is always included.
*/
$max_lookback = 1800; // 30 min
/**
* How far in the future to query for additional data. For example, if a
* sample ends 20 minutes prior to an event change, I need to look ahead
* to see if an event change is in the future. If so, I need to adjust for
* that because the sensor averages will already be wrong.
*/
$max_lookahead = 1800; // 30 min
// Get some stuff
$thermostat = $this->api('thermostat', 'get', $thermostat_id);
// Figure out all the starting and ending times. Round begin/end to the
// nearest 5 minutes to help with the looping later on.
$end_timestamp = time();
$begin_timestamp = strtotime('-1 year', $end_timestamp);
// Round to 5 minute intervals.
$begin_timestamp = floor($begin_timestamp / 300) * 300;
$end_timestamp = floor($end_timestamp / 300) * 300;
$group_thermostats = $this->api(
'thermostat',
'read',
[
'attributes' => [
'thermostat_group_id' => $thermostat['thermostat_group_id'],
'inactive' => 0
]
]
);
// Get all of the relevant data
$thermostat_ids = [];
foreach($group_thermostats as $thermostat) {
$thermostat_ids[] = $thermostat['thermostat_id'];
}
/**
* Get the largest possible chunk size given the number of thermostats I
* have to select data for. This is necessary to prevent the script from
* running out of memory. Also, as of PHP 7, structures have 6-7x of
* memory overhead.
*/
$memory_limit = 16; // mb
$memory_per_thermostat_per_day = 0.6; // mb
$days = (int) floor($memory_limit / ($memory_per_thermostat_per_day * count($thermostat_ids)));
$chunk_size = $days * 86400;
if($chunk_size === 0) {
throw new Exception('Too many thermostats; cannot generate temperature profile.', 10301);
}
$current_timestamp = $begin_timestamp;
$chunk_end_timestamp = 0;
$five_minutes = 300;
$thirty_minutes = 1800;
$all_off_for = 0;
$cool_on_for = 0;
$heat_on_for = 0;
$samples = [];
$times = [
'heat' => [],
'cool' => [],
'resist' => []
];
$begin_runtime = [];
while($current_timestamp <= $end_timestamp) {
// Get a new chunk of data.
if($current_timestamp >= $chunk_end_timestamp) {
$chunk_end_timestamp = $current_timestamp + $chunk_size;
$query = '
select
`timestamp`,
`thermostat_id`,
`indoor_temperature`,
`outdoor_temperature`,
`compressor_1`,
`compressor_2`,
`compressor_mode`,
`auxiliary_heat_1`,
`auxiliary_heat_2`,
`event_runtime_thermostat_text_id`,
`climate_runtime_thermostat_text_id`
from
`runtime_thermostat`
where
`thermostat_id` in (' . implode(',', $thermostat_ids) . ')
and `timestamp` >= "' . date('Y-m-d H:i:s', ($current_timestamp - $max_lookback)) . '"
and `timestamp` < "' . date('Y-m-d H:i:s', ($chunk_end_timestamp + $max_lookahead)) . '"
';
$result = $this->database->query($query);
$runtime = [];
while($row = $result->fetch_assoc()) {
if(
$thermostat['system_type']['detected']['heat'] === 'compressor' ||
$thermostat['system_type']['detected']['heat'] === 'geothermal'
) {
if($row['compressor_mode'] === 'heat') {
$row['heat'] = max(
$row['compressor_1'],
$row['compressor_2']
);
} else {
$row['heat'] = 0;
}
$row['auxiliary_heat'] = max(
$row['auxiliary_heat_1'],
$row['auxiliary_heat_2']
);
} else {
$row['heat'] = max(
$row['auxiliary_heat_1'],
$row['auxiliary_heat_2']
);
$row['auxiliary_heat'] = 0;
}
if($row['compressor_mode'] === 'cool') {
$row['cool'] = max(
$row['compressor_1'],
$row['compressor_2']
);
} else {
$row['cool'] = 0;
}
$timestamp = strtotime($row['timestamp']);
if (isset($runtime[$timestamp]) === false) {
$runtime[$timestamp] = [];
}
$runtime[$timestamp][$row['thermostat_id']] = $row;
}
}
if(
isset($runtime[$current_timestamp]) === true && // Had data for at least one thermostat
isset($runtime[$current_timestamp][$thermostat_id]) === true // Had data for the requested thermostat
) {
$current_runtime = $runtime[$current_timestamp][$thermostat_id];
if($current_runtime['outdoor_temperature'] !== null) {
// Rounds to the nearest degree (because temperatures are stored in tenths).
$current_runtime['outdoor_temperature'] = round($current_runtime['outdoor_temperature'] / 10) * 10;
// Applies further smoothing if required.
$current_runtime['outdoor_temperature'] = round($current_runtime['outdoor_temperature'] / $smoothing) * $smoothing;
}
/**
* OFF START
*/
$most_off = true;
$all_off = true;
if(
count($runtime[$current_timestamp]) < count($thermostat_ids)
) {
// If I didn't get data at this timestamp for all thermostats in the
// group, all off can't be true.
$all_off = false;
$most_off = false;
}
else {
foreach($runtime[$current_timestamp] as $runtime_thermostat_id => $thermostat_runtime) {
if(
$thermostat_runtime['compressor_1'] !== 0 ||
$thermostat_runtime['compressor_2'] !== 0 ||
$thermostat_runtime['auxiliary_heat_1'] !== 0 ||
$thermostat_runtime['auxiliary_heat_2'] !== 0 ||
$thermostat_runtime['outdoor_temperature'] === null ||
$thermostat_runtime['indoor_temperature'] === null ||
(
// Wasn't syncing this until mid-November 2018. Just going with December to be safe.
$thermostat_runtime['climate_runtime_thermostat_text_id'] === null &&
$current_timestamp > 1543640400
)
) {
// If I did have data at this timestamp for all thermostats in the
// group, check and see if were fully off. Also if any of the
// things used in the algorithm are just missing, assume the
// system might have been running.
$all_off = false;
// If everything _but_ the requested thermostat is off. This is
// used for the heat/cool scores as I need to only gather samples
// when everything else is off.
if($runtime_thermostat_id !== $thermostat_id) {
$most_off = false;
}
}
}
}
// Assume that the runtime rows represent data at the end of that 5
// minutes.
if($all_off === true) {
$all_off_for += $five_minutes;
// Store the begin runtime row if the system has been off for the
// requisite length. This gives the temperatures a chance to settle.
if($all_off_for === $minimum_off_for) {
$begin_runtime['resist'] = $current_runtime;
}
}
else {
$all_off_for = 0;
}
/**
* HEAT START
*/
// Track how long the heat has been on for.
if($current_runtime['heat'] > 0) {
$heat_on_for += $current_runtime['heat'];
} else {
if($heat_on_for > 0) {
$times['heat'][] = $heat_on_for;
}
$heat_on_for = 0;
}
// Store the begin runtime for heat when the heat has been on for this
// thermostat only for the required minimum and everything else is off.
if(
$most_off === true &&
$heat_on_for >= $minimum_on_for &&
$current_runtime['auxiliary_heat'] === 0 &&
isset($begin_runtime['heat']) === false
) {
$begin_runtime['heat'] = $current_runtime;
}
/**
* COOL START
*/
// Track how long the cool has been on for.
if($current_runtime['cool'] > 0) {
$cool_on_for += $current_runtime['cool'];
} else {
if($cool_on_for > 0) {
$times['cool'][] = $cool_on_for;
}
$cool_on_for = 0;
}
// Store the begin runtime for cool when the cool has been on for this
// thermostat only for the required minimum and everything else is off.
if(
$most_off === true &&
$cool_on_for >= $minimum_on_for &&
isset($begin_runtime['cool']) === false
) {
$begin_runtime['cool'] = $current_runtime;
}
// Look for changes which would trigger a sample to be gathered.
if(
(
// Heat
// Gather a "heat" delta for one of the following reasons.
// - The outdoor temperature changed
// - The calendar event changed
// - The climate changed
// - One of the other thermostats in this group turned on
($sample_type = 'heat') &&
isset($begin_runtime['heat']) === true &&
isset($previous_runtime) === true &&
(
$current_runtime['outdoor_temperature'] !== $begin_runtime['heat']['outdoor_temperature'] ||
$current_runtime['event_runtime_thermostat_text_id'] !== $begin_runtime['heat']['event_runtime_thermostat_text_id'] ||
$current_runtime['climate_runtime_thermostat_text_id'] !== $begin_runtime['heat']['climate_runtime_thermostat_text_id'] ||
$most_off === false
)
) ||
(
// Cool
// Gather a "cool" delta for one of the following reasons.
// - The outdoor temperature changed
// - The calendar event changed
// - The climate changed
// - One of the other thermostats in this group turned on
($sample_type = 'cool') &&
isset($begin_runtime['cool']) === true &&
isset($previous_runtime) === true &&
(
$current_runtime['outdoor_temperature'] !== $begin_runtime['cool']['outdoor_temperature'] ||
$current_runtime['event_runtime_thermostat_text_id'] !== $begin_runtime['cool']['event_runtime_thermostat_text_id'] ||
$current_runtime['climate_runtime_thermostat_text_id'] !== $begin_runtime['cool']['climate_runtime_thermostat_text_id'] ||
$most_off === false
)
) ||
(
// Resist
// Gather an "off" delta for one of the following reasons.
// - The outdoor temperature changed
// - The calendar event changed
// - The climate changed
// - The system turned back on after being off
($sample_type = 'resist') &&
isset($begin_runtime['resist']) === true &&
isset($previous_runtime) === true &&
(
$current_runtime['outdoor_temperature'] !== $begin_runtime['resist']['outdoor_temperature'] ||
$current_runtime['event_runtime_thermostat_text_id'] !== $begin_runtime['resist']['event_runtime_thermostat_text_id'] ||
$current_runtime['climate_runtime_thermostat_text_id'] !== $begin_runtime['resist']['climate_runtime_thermostat_text_id'] ||
$all_off === false
)
)
) {
// By default the end sample is the previous sample (five minutes ago).
$offset = $five_minutes;
// If event_runtime_thermostat_text_id or climate_runtime_thermostat_text_id changes, need to ignore data
// from the previous 30 minutes as there are sensors changing during
// that time.
if(
$current_runtime['event_runtime_thermostat_text_id'] !== $begin_runtime[$sample_type]['event_runtime_thermostat_text_id'] ||
$current_runtime['climate_runtime_thermostat_text_id'] !== $begin_runtime[$sample_type]['climate_runtime_thermostat_text_id']
) {
$offset = $thirty_minutes;
} else {
// Start looking ahead into the next 30 minutes looking for changes
// to event_runtime_thermostat_text_id and climate_runtime_thermostat_text_id.
$lookahead = $five_minutes;
while($lookahead <= $thirty_minutes) {
if(
isset($runtime[$current_timestamp + $lookahead]) === true &&
isset($runtime[$current_timestamp + $lookahead][$thermostat_id]) === true &&
(
$runtime[$current_timestamp + $lookahead][$thermostat_id]['event_runtime_thermostat_text_id'] !== $current_runtime['event_runtime_thermostat_text_id'] ||
$runtime[$current_timestamp + $lookahead][$thermostat_id]['climate_runtime_thermostat_text_id'] !== $current_runtime['climate_runtime_thermostat_text_id']
)
) {
$offset = ($thirty_minutes - $lookahead);
break;
}
$lookahead += $five_minutes;
}
}
// Now use the offset to set the proper end_runtime. This simply makes
// sure the data is present and then uses it. In the case where the
// desired data is missing, I *could* look back further but I'm not
// going to bother. It's pretty rare and adds some unwanted complexity
// to this.
if(
isset($runtime[$current_timestamp - $offset]) === true &&
isset($runtime[$current_timestamp - $offset][$thermostat_id]) === true &&
($current_timestamp - $offset) > strtotime($begin_runtime[$sample_type]['timestamp'])
) {
$end_runtime = $runtime[$current_timestamp - $offset][$thermostat_id];
} else {
$end_runtime = null;
}
if($end_runtime !== null) {
$delta = $end_runtime['indoor_temperature'] - $begin_runtime[$sample_type]['indoor_temperature'];
$duration = strtotime($end_runtime['timestamp']) - strtotime($begin_runtime[$sample_type]['timestamp']);
if($duration > 0) {
$sample = [
'type' => $sample_type,
'outdoor_temperature' => $begin_runtime[$sample_type]['outdoor_temperature'],
'delta' => $delta,
'duration' => $duration,
'delta_per_hour' => $delta / $duration * 3600,
];
$samples[] = $sample;
}
}
// If in this block of code a change in runtime was detected, so
// update $begin_runtime[$sample_type] to the current runtime.
$begin_runtime[$sample_type] = $current_runtime;
}
$previous_runtime = $current_runtime;
}
// After a change was detected it automatically moves begin to the
// current_runtime to start a new sample. This might be invalid so need to
// unset it if so.
if(
$heat_on_for === 0 ||
$current_runtime['outdoor_temperature'] === null ||
$current_runtime['indoor_temperature'] === null ||
$current_runtime['auxiliary_heat'] > 0
) {
unset($begin_runtime['heat']);
}
if(
$cool_on_for === 0 ||
$current_runtime['outdoor_temperature'] === null ||
$current_runtime['indoor_temperature'] === null
) {
unset($begin_runtime['cool']);
}
if($all_off_for === 0) {
unset($begin_runtime['resist']);
}
$current_timestamp += $five_minutes;
}
// Process the samples
$deltas_raw = [];
foreach($samples as $sample) {
$is_valid_sample = true;
if($sample['duration'] < $minimum_sample_duration[$sample['type']]) {
$is_valid_sample = false;
}
if($is_valid_sample === true) {
if(isset($deltas_raw[$sample['type']]) === false) {
$deltas_raw[$sample['type']] = [];
}
if(isset($deltas_raw[$sample['type']][$sample['outdoor_temperature']]) === false) {
$deltas_raw[$sample['type']][$sample['outdoor_temperature']] = [
'deltas_per_hour' => []
];
}
$deltas_raw[$sample['type']][$sample['outdoor_temperature']]['deltas_per_hour'][] = $sample['delta_per_hour'];
}
}
$deltas = [];
foreach($deltas_raw as $type => $raw) {
if(isset($deltas[$type]) === false) {
$deltas[$type] = [];
}
foreach($raw as $outdoor_temperature => $data) {
if(
isset($deltas[$type][$outdoor_temperature]) === false &&
count($data['deltas_per_hour']) >= $required_samples
) {
$deltas[$type][$outdoor_temperature] = round(array_median($data['deltas_per_hour']), 2);
}
}
}
// Generate the final temperature profile and save it.
$temperature_profile = [];
foreach($deltas as $type => $data) {
if(count($data) < $required_points) {
continue;
}
ksort($deltas[$type]);
// For heating/cooling, factor in cycle time.
if(count($times[$type]) > 0) {
$cycles_per_hour = round(60 / (array_median($times[$type]) / 60), 2);
} else {
$cycles_per_hour = null;
}
$linear_trendline = $this->api(
'temperature_profile',
'get_linear_trendline',
[
'data' => $deltas[$type]
]
);
$temperature_profile[$type] = [
'deltas' => $deltas[$type],
'linear_trendline' => $linear_trendline,
'cycles_per_hour' => $cycles_per_hour,
'metadata' => [
'generated_at' => date('Y-m-d H:i:s')
]
];
$temperature_profile[$type]['score'] = $this->api(
'temperature_profile',
'get_score',
[
'type' => $type,
'temperature_profile' => $temperature_profile[$type]
]
);
}
// Only actually save this profile to the thermostat if it was run with the
// default settings (aka the last year). Anything else is not valid to save.
// if($save === true) {
$this->api(
'thermostat',
'update',
[
'attributes' => [
'thermostat_id' => $thermostat['thermostat_id'],
'temperature_profile' => $temperature_profile
]
]
);
// }
$this->database->set_time_zone(0);
// Force these to actually return, but set them to null if there's no data.
foreach(['heat', 'cool', 'resist'] as $type) {
if(
isset($temperature_profile[$type]) === false ||
count($temperature_profile[$type]['deltas']) === 0
) {
$temperature_profile[$type] = null;
}
}
return $temperature_profile;
}
/**
* Get the properties of a linear trendline for a given set of data.
*
* @param array $data
*
* @return array [slope, intercept]
*/
public function get_linear_trendline($data) {
// Requires at least two points.
if(count($data) < 2) {
return null;
}
$sum_x = 0;
$sum_y = 0;
$sum_xy = 0;
$sum_x_squared = 0;
$n = 0;
foreach($data as $x => $y) {
$sum_x += $x;
$sum_y += $y;
$sum_xy += ($x * $y);
$sum_x_squared += pow($x, 2);
$n++;
}
$slope = (($n * $sum_xy) - ($sum_x * $sum_y)) / (($n * $sum_x_squared) - (pow($sum_x, 2)));
$intercept = (($sum_y) - ($slope * $sum_x)) / ($n);
return [
'slope' => round($slope, 2),
'intercept' => round($intercept, 2)
];
}
/**
* Get the score from a linear trendline. For heating and cooling the slope
* is most of the score. For resist it is all of the score.
*
* Slope score is calculated as a percentage between 0 and whatever 3
* standard deviations from the mean is. For example, if that gives a range
* from 0-5, a slope of 2.5 would give you a base score of 0.5 which is then
* weighted in with the rest of the factors.
*
* Cycles per hour score is calculated as a flat 0.25 base score for every
* CPH under 4. For example, a CPH of 1
*
* @param array $temperature_profile
*
* @return int
*/
public function get_score($type, $temperature_profile) {
if(
$temperature_profile['linear_trendline'] === null
) {
return null;
}
$weights = [
'heat' => [
'slope' => 0.6,
'cycles_per_hour' => 0.1,
'balance_point' => 0.3
],
'cool' => [
'slope' => 0.6,
'cycles_per_hour' => 0.1,
'balance_point' => 0.3
],
'resist' => [
'slope' => 1
]
];
// Slope score
switch($type) {
case 'heat':
$slope_mean = 0.042;
$slope_standard_deviation = 0.179;
$balance_point_mean = -12.235;
// This is arbitrary. The actual SD is really high due to what I think
// is poor data. Further investigating but for now this does a pretty
// good job.
$balance_point_standard_deviation = 20;
break;
case 'cool':
$slope_mean = 0.066;
$slope_standard_deviation = 0.29;
$balance_point_mean = 90.002;
// This is arbitrary. The actual SD is really high due to what I think
// is poor data. Further investigating but for now this does a pretty
// good job.
$balance_point_standard_deviation = 20;
break;
case 'resist':
$slope_mean = 0.034;
$slope_standard_deviation = 0.018;
break;
}
$parts = [];
$slope_max = $slope_mean + ($slope_standard_deviation * 3);
$parts['slope'] = ($slope_max - $temperature_profile['linear_trendline']['slope']) / $slope_max;
$parts['slope'] = max(0, min(1, $parts['slope']));
if($type === 'heat' || $type === 'cool') {
if($temperature_profile['linear_trendline']['slope'] == 0) {
$parts['balance_point'] = 1;
} else {
$balance_point_min = $balance_point_mean - ($balance_point_standard_deviation * 3);
$balance_point_max = $balance_point_mean + ($balance_point_standard_deviation * 3);
$balance_point = -$temperature_profile['linear_trendline']['intercept'] / $temperature_profile['linear_trendline']['slope'];
$parts['balance_point'] = ($balance_point - $balance_point_min) / ($balance_point_max - $balance_point_min);
$parts['balance_point'] = max(0, min(1, $parts['balance_point']));
}
}
// Cycles per hour score
if($temperature_profile['cycles_per_hour'] !== null) {
$parts['cycles_per_hour'] = (4 - $temperature_profile['cycles_per_hour']) * 0.25;
$parts['cycles_per_hour'] = max(0, min(1, $parts['cycles_per_hour']));
}
$score = 0;
foreach($parts as $key => $value) {
$score += $value * $weights[$type][$key];
}
return round($score * 10, 1);
}
}