Wrap null-gap detect and fill in async gen
Call it `iter_null_segs()` (for now?) and use in the final (sequential)
stage of the `.history.start_backfill()` task-func. Delivers abs,
frame-relative, and equiv time stamps on each iteration pertaining to
each detected null-segment to make it easy to do piece-wise history
queries for each.
Further,
- handle edge case in `get_null_segs()` where there is only 1 zeroed
row value, in which case we deliver `absi_zsegs` as a single pair of
the same index value and,
- when this occurs `iter_null_seqs()` delivers `None` for all the
`start_` related indices/timestamps since all `get_hist()` routines
(delivered by `open_history_client()`) should handle it as being a
"get max history from this end_dt" type query.
- add note about needing to do time gap handling where there's a gap in
the timeseries-history that isn't actually IN the data-history.
distribute_dis
Tyler Goodlet
parent
c129f5bb4a
commit
83bdca46a2
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@ -59,9 +59,10 @@ from ._sampling import (
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from .tsp import (
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dedupe,
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get_null_segs,
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iter_null_segs,
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sort_diff,
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Frame,
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Seq,
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# Seq,
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)
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from ..brokers._util import (
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DataUnavailable,
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@ -174,38 +175,22 @@ async def maybe_fill_null_segments(
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) -> list[Frame]:
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frame: Frame = shm.array
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null_segs: tuple | None = get_null_segs(
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async for (
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absi_start, absi_end,
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fi_start, fi_end,
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start_t, end_t,
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start_dt, end_dt,
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) in iter_null_segs(
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frame,
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period=timeframe,
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)
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if null_segs:
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absi_pairs_zsegs: list[list[float, float]]
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izeros: Seq
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zero_t: Frame
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(
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absi_pairs_zsegs,
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izeros,
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zero_t,
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) = null_segs
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timeframe=timeframe,
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):
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absi_first: int = frame[0]['index']
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for absi_start, absi_end in absi_pairs_zsegs:
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# await tractor.pause()
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fi_start = absi_start - absi_first
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fi_end = absi_end - absi_first
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start_row: Seq = frame[fi_start]
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end_row: Seq = frame[fi_end]
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start_t: float = start_row['time']
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end_t: float = end_row['time']
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start_dt = from_timestamp(start_t)
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end_dt = from_timestamp(end_t)
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# if we get a badly ordered timestamp
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# pair, immediately stop backfilling.
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if end_dt < start_dt:
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# XXX NOTE: ?if we get a badly ordered timestamp
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# pair, immediately stop backfilling?
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if (
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start_dt
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and end_dt < start_dt
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):
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break
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(
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@ -231,7 +216,6 @@ async def maybe_fill_null_segments(
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prepend_index=absi_end,
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update_start_on_prepend=False,
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)
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# TODO: UI side needs IPC event to update..
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# - make sure the UI actually always handles
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# this update!
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@ -240,10 +224,23 @@ async def maybe_fill_null_segments(
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# loop
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await sampler_stream.send({
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'broadcast_all': {
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# XXX NOTE XXX: see the
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# `.ui._display.increment_history_view()` if block
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# that looks for this info to FORCE a hard viz
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# redraw!
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'backfilling': (mkt.fqme, timeframe),
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},
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})
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await tractor.pause()
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# TODO: interatively step through any remaining time gaps?
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# if (
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# next_end_dt not in frame[
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# ):
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# pass
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# RECHECK for more null-gaps
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frame: Frame = shm.array
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null_segs: tuple | None = get_null_segs(
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@ -29,10 +29,17 @@ from math import (
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floor,
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)
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import time
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from typing import Literal
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from typing import (
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Literal,
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AsyncGenerator,
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)
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import numpy as np
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import polars as pl
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from pendulum import (
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DateTime,
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from_timestamp,
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)
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from ..toolz.profile import (
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Profiler,
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@ -223,7 +230,10 @@ def get_null_segs(
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col: str = 'time',
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) -> tuple[
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Seq,
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# Seq, # TODO: can we make it an array-type instead?
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list[
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list[int, int],
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],
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Seq,
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Frame
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] | None:
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@ -285,13 +295,27 @@ def get_null_segs(
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# select out slice index pairs for each null-segment
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# portion detected throughout entire input frame.
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# import pdbp; pdbp.set_trace()
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# only one null-segment in entire frame?
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if not fi_zgaps.size:
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# check for number null rows
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# TODO: use ndarray for this!
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if absi_zeros.size > 1:
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absi_zsegs = [[
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absi_zeros[0], # - 1, # - ifirst,
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# TODO: need the + 1 or no?
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absi_zeros[-1] + 1, # - ifirst,
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]]
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else:
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absi_zsegs = [[
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# absi_zeros[0] + 1,
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# see `get_hist()` in backend, should ALWAYS be
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# able to handle a `start_dt=None`!
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None,
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absi_zeros[0] + 1,
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]]
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else:
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absi_zsegs.append([
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absi_zeros[0] - 1, # - ifirst,
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@ -305,15 +329,12 @@ def get_null_segs(
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) in enumerate(zip(
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fi_zgaps,
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fi_zseg_start_rows,
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# fi_zgaps,
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# start=1,
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)):
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assert (zseg_start_row == zero_t[fi]).all()
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absi: int = zseg_start_row['index'][0]
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# row = zero_t[fi]
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# absi_pre_zseg = row['index'][0] - 1
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absi_pre_zseg = absi - 1
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# absi_pre_zseg = absi - 1
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if i > 0:
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prev_zseg_row = zero_t[fi - 1]
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@ -330,7 +351,6 @@ def get_null_segs(
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assert end
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assert start < end
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# import pdbp; pdbp.set_trace()
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return (
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absi_zsegs, # start indices of null
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absi_zeros,
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@ -338,6 +358,69 @@ def get_null_segs(
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)
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async def iter_null_segs(
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frame: Frame,
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timeframe: float,
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) -> AsyncGenerator[
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tuple[
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int, int,
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int, int,
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float, float,
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float, float,
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# Seq, # TODO: can we make it an array-type instead?
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# list[
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# list[int, int],
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# ],
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# Seq,
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# Frame
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],
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None,
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]:
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if null_segs := get_null_segs(
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frame,
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period=timeframe,
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):
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absi_pairs_zsegs: list[list[float, float]]
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izeros: Seq
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zero_t: Frame
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(
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absi_pairs_zsegs,
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izeros,
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zero_t,
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) = null_segs
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absi_first: int = frame[0]['index']
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for (
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absi_start,
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absi_end,
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) in absi_pairs_zsegs:
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fi_end: int = absi_end - absi_first
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end_row: Seq = frame[fi_end]
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end_t: float = end_row['time']
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end_dt: DateTime = from_timestamp(end_t)
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if absi_start is not None:
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fi_start: int = absi_start - absi_first
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start_row: Seq = frame[fi_start]
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start_t: float = start_row['time']
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start_dt: DateTime = from_timestamp(start_t)
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else:
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fi_start = None
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start_row = None
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start_t = None
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start_dt = None
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yield (
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absi_start, absi_end, # abs indices
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fi_start, fi_end, # relative "frame" indices
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start_t, end_t,
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start_dt, end_dt,
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)
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def with_dts(
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df: pl.DataFrame,
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time_col: str = 'time',
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Loading…
Reference in New Issue