Files
daqbuffer/items/src/minmaxavgwavebins.rs
2021-12-17 18:23:51 +01:00

432 lines
12 KiB
Rust

use crate::numops::NumOps;
use crate::streams::{Collectable, Collector, ToJsonBytes, ToJsonResult};
use crate::{
ts_offs_from_abs, Appendable, FilterFittingInside, Fits, FitsInside, IsoDateTime, RangeOverlapInfo, ReadPbv,
ReadableFromFile, Sitemty, SitemtyFrameType, SubFrId, TimeBinnableType, TimeBinnableTypeAggregator, TimeBins,
WithLen,
};
use chrono::{TimeZone, Utc};
use err::Error;
use netpod::timeunits::SEC;
use netpod::NanoRange;
use num_traits::Zero;
use serde::{Deserialize, Serialize};
use std::fmt;
use std::marker::PhantomData;
use tokio::fs::File;
#[derive(Serialize, Deserialize)]
pub struct MinMaxAvgWaveBins<NTY> {
pub ts1s: Vec<u64>,
pub ts2s: Vec<u64>,
pub counts: Vec<u64>,
pub mins: Vec<Option<Vec<NTY>>>,
pub maxs: Vec<Option<Vec<NTY>>>,
pub avgs: Vec<Option<Vec<f32>>>,
}
impl<NTY> SitemtyFrameType for MinMaxAvgWaveBins<NTY>
where
NTY: SubFrId,
{
const FRAME_TYPE_ID: u32 = 0xa00 + NTY::SUB;
}
impl<NTY> fmt::Debug for MinMaxAvgWaveBins<NTY>
where
NTY: fmt::Debug,
{
fn fmt(&self, fmt: &mut fmt::Formatter) -> fmt::Result {
write!(
fmt,
"MinMaxAvgWaveBins count {} ts1s {:?} ts2s {:?} counts {:?} mins {:?} maxs {:?} avgs {:?}",
self.ts1s.len(),
self.ts1s.iter().map(|k| k / SEC).collect::<Vec<_>>(),
self.ts2s.iter().map(|k| k / SEC).collect::<Vec<_>>(),
self.counts,
self.mins,
self.maxs,
self.avgs,
)
}
}
impl<NTY> MinMaxAvgWaveBins<NTY> {
pub fn empty() -> Self {
Self {
ts1s: vec![],
ts2s: vec![],
counts: vec![],
mins: vec![],
maxs: vec![],
avgs: vec![],
}
}
}
impl<NTY> FitsInside for MinMaxAvgWaveBins<NTY> {
fn fits_inside(&self, range: NanoRange) -> Fits {
if self.ts1s.is_empty() {
Fits::Empty
} else {
let t1 = *self.ts1s.first().unwrap();
let t2 = *self.ts2s.last().unwrap();
if t2 <= range.beg {
Fits::Lower
} else if t1 >= range.end {
Fits::Greater
} else if t1 < range.beg && t2 > range.end {
Fits::PartlyLowerAndGreater
} else if t1 < range.beg {
Fits::PartlyLower
} else if t2 > range.end {
Fits::PartlyGreater
} else {
Fits::Inside
}
}
}
}
impl<NTY> FilterFittingInside for MinMaxAvgWaveBins<NTY> {
fn filter_fitting_inside(self, fit_range: NanoRange) -> Option<Self> {
match self.fits_inside(fit_range) {
Fits::Inside | Fits::PartlyGreater | Fits::PartlyLower | Fits::PartlyLowerAndGreater => Some(self),
_ => None,
}
}
}
impl<NTY> RangeOverlapInfo for MinMaxAvgWaveBins<NTY> {
fn ends_before(&self, range: NanoRange) -> bool {
match self.ts2s.last() {
Some(&ts) => ts <= range.beg,
None => true,
}
}
fn ends_after(&self, range: NanoRange) -> bool {
match self.ts2s.last() {
Some(&ts) => ts > range.end,
None => panic!(),
}
}
fn starts_after(&self, range: NanoRange) -> bool {
match self.ts1s.first() {
Some(&ts) => ts >= range.end,
None => panic!(),
}
}
}
impl<NTY> TimeBins for MinMaxAvgWaveBins<NTY>
where
NTY: NumOps,
{
fn ts1s(&self) -> &Vec<u64> {
&self.ts1s
}
fn ts2s(&self) -> &Vec<u64> {
&self.ts2s
}
}
impl<NTY> WithLen for MinMaxAvgWaveBins<NTY> {
fn len(&self) -> usize {
self.ts1s.len()
}
}
impl<NTY> Appendable for MinMaxAvgWaveBins<NTY>
where
NTY: NumOps,
{
fn empty() -> Self {
Self::empty()
}
fn append(&mut self, src: &Self) {
self.ts1s.extend_from_slice(&src.ts1s);
self.ts2s.extend_from_slice(&src.ts2s);
self.counts.extend_from_slice(&src.counts);
self.mins.extend_from_slice(&src.mins);
self.maxs.extend_from_slice(&src.maxs);
self.avgs.extend_from_slice(&src.avgs);
}
}
impl<NTY> ReadableFromFile for MinMaxAvgWaveBins<NTY>
where
NTY: NumOps,
{
// TODO this function is not needed in the trait:
fn read_from_file(file: File) -> Result<ReadPbv<Self>, Error> {
Ok(ReadPbv::new(file))
}
fn from_buf(buf: &[u8]) -> Result<Self, Error> {
let dec = serde_cbor::from_slice(&buf)?;
Ok(dec)
}
}
impl<NTY> TimeBinnableType for MinMaxAvgWaveBins<NTY>
where
NTY: NumOps,
{
type Output = MinMaxAvgWaveBins<NTY>;
type Aggregator = MinMaxAvgWaveBinsAggregator<NTY>;
fn aggregator(range: NanoRange, x_bin_count: usize, _do_time_weight: bool) -> Self::Aggregator {
Self::Aggregator::new(range, x_bin_count)
}
}
impl<NTY> ToJsonResult for Sitemty<MinMaxAvgWaveBins<NTY>>
where
NTY: NumOps,
{
fn to_json_result(&self) -> Result<Box<dyn ToJsonBytes>, Error> {
Ok(Box::new(serde_json::Value::String(format!(
"MinMaxAvgBins/non-json-item"
))))
}
}
pub struct MinMaxAvgWaveBinsCollected<NTY> {
_m1: PhantomData<NTY>,
}
impl<NTY> MinMaxAvgWaveBinsCollected<NTY> {
pub fn new() -> Self {
Self { _m1: PhantomData }
}
}
#[derive(Serialize)]
pub struct MinMaxAvgWaveBinsCollectedResult<NTY> {
#[serde(rename = "tsAnchor")]
ts_anchor_sec: u64,
#[serde(rename = "tsMs")]
ts_off_ms: Vec<u64>,
#[serde(rename = "tsNs")]
ts_off_ns: Vec<u64>,
counts: Vec<u64>,
mins: Vec<Option<Vec<NTY>>>,
maxs: Vec<Option<Vec<NTY>>>,
avgs: Vec<Option<Vec<f32>>>,
#[serde(skip_serializing_if = "crate::bool_is_false", rename = "finalisedRange")]
finalised_range: bool,
#[serde(skip_serializing_if = "Zero::is_zero", rename = "missingBins")]
missing_bins: u32,
#[serde(skip_serializing_if = "Option::is_none", rename = "continueAt")]
continue_at: Option<IsoDateTime>,
}
pub struct MinMaxAvgWaveBinsCollector<NTY> {
bin_count_exp: u32,
timed_out: bool,
range_complete: bool,
vals: MinMaxAvgWaveBins<NTY>,
_m1: PhantomData<NTY>,
}
impl<NTY> MinMaxAvgWaveBinsCollector<NTY> {
pub fn new(bin_count_exp: u32) -> Self {
Self {
bin_count_exp,
timed_out: false,
range_complete: false,
vals: MinMaxAvgWaveBins::<NTY>::empty(),
_m1: PhantomData,
}
}
}
impl<NTY> WithLen for MinMaxAvgWaveBinsCollector<NTY>
where
NTY: NumOps + Serialize,
{
fn len(&self) -> usize {
self.vals.ts1s.len()
}
}
impl<NTY> Collector for MinMaxAvgWaveBinsCollector<NTY>
where
NTY: NumOps + Serialize,
{
type Input = MinMaxAvgWaveBins<NTY>;
type Output = MinMaxAvgWaveBinsCollectedResult<NTY>;
fn ingest(&mut self, src: &Self::Input) {
Appendable::append(&mut self.vals, src);
}
fn set_range_complete(&mut self) {
self.range_complete = true;
}
fn set_timed_out(&mut self) {
self.timed_out = true;
}
fn result(self) -> Result<Self::Output, Error> {
let t_bin_count = self.vals.counts.len();
// TODO could save the copy:
let mut ts_all = self.vals.ts1s.clone();
if self.vals.ts2s.len() > 0 {
ts_all.push(*self.vals.ts2s.last().unwrap());
}
let continue_at = if self.vals.ts1s.len() < self.bin_count_exp as usize {
match ts_all.last() {
Some(&k) => {
let iso = IsoDateTime(Utc.timestamp_nanos(k as i64));
Some(iso)
}
None => Err(Error::with_msg("partial_content but no bin in result"))?,
}
} else {
None
};
let tst = ts_offs_from_abs(&ts_all);
let ret = MinMaxAvgWaveBinsCollectedResult {
ts_anchor_sec: tst.0,
ts_off_ms: tst.1,
ts_off_ns: tst.2,
counts: self.vals.counts,
mins: self.vals.mins,
maxs: self.vals.maxs,
avgs: self.vals.avgs,
finalised_range: self.range_complete,
missing_bins: self.bin_count_exp - t_bin_count as u32,
continue_at,
};
Ok(ret)
}
}
impl<NTY> Collectable for MinMaxAvgWaveBins<NTY>
where
NTY: NumOps + Serialize,
{
type Collector = MinMaxAvgWaveBinsCollector<NTY>;
fn new_collector(bin_count_exp: u32) -> Self::Collector {
Self::Collector::new(bin_count_exp)
}
}
pub struct MinMaxAvgWaveBinsAggregator<NTY> {
range: NanoRange,
count: u64,
min: Vec<NTY>,
max: Vec<NTY>,
sum: Vec<f32>,
sumc: u64,
}
impl<NTY> MinMaxAvgWaveBinsAggregator<NTY>
where
NTY: NumOps,
{
pub fn new(range: NanoRange, x_bin_count: usize) -> Self {
Self {
range,
count: 0,
min: vec![NTY::max_or_nan(); x_bin_count],
max: vec![NTY::min_or_nan(); x_bin_count],
sum: vec![0f32; x_bin_count],
sumc: 0,
}
}
}
impl<NTY> TimeBinnableTypeAggregator for MinMaxAvgWaveBinsAggregator<NTY>
where
NTY: NumOps,
{
type Input = MinMaxAvgWaveBins<NTY>;
type Output = MinMaxAvgWaveBins<NTY>;
fn range(&self) -> &NanoRange {
&self.range
}
fn ingest(&mut self, item: &Self::Input) {
for i1 in 0..item.ts1s.len() {
if item.ts2s[i1] <= self.range.beg {
continue;
} else if item.ts1s[i1] >= self.range.end {
continue;
} else {
// the input can contain bins where no events did fall into.
match &item.mins[i1] {
None => {}
Some(inp) => {
for (a, b) in self.min.iter_mut().zip(inp.iter()) {
if *b < *a || a.is_nan() {
*a = *b;
}
}
}
}
match &item.maxs[i1] {
None => {}
Some(inp) => {
for (a, b) in self.max.iter_mut().zip(inp.iter()) {
if *b > *a || a.is_nan() {
*a = *b;
}
}
}
}
match &item.avgs[i1] {
None => {}
Some(inp) => {
for (a, b) in self.sum.iter_mut().zip(inp.iter()) {
*a += *b;
}
}
}
self.sumc += 1;
self.count += item.counts[i1];
}
}
}
fn result_reset(&mut self, range: NanoRange, _expand: bool) -> Self::Output {
let ret;
if self.sumc == 0 {
ret = Self::Output {
ts1s: vec![self.range.beg],
ts2s: vec![self.range.end],
counts: vec![self.count],
mins: vec![None],
maxs: vec![None],
avgs: vec![None],
};
} else {
let avg = self.sum.iter().map(|j| *j / self.sumc as f32).collect();
ret = Self::Output {
ts1s: vec![self.range.beg],
ts2s: vec![self.range.end],
counts: vec![self.count],
// TODO replace with reset-value instead:
mins: vec![Some(self.min.clone())],
maxs: vec![Some(self.max.clone())],
avgs: vec![Some(avg)],
};
}
self.range = range;
self.count = 0;
self.min = vec![NTY::max_or_nan(); self.min.len()];
self.max = vec![NTY::min_or_nan(); self.min.len()];
self.sum = vec![0f32; self.min.len()];
self.sumc = 0;
ret
}
}