Make `LinearRegion` link using epoch-time index
Turned out to be super simple to get the first draft to work since the fast and slow chart now use the same domain, however, it seems like maybe there's an offset issue still where the fast may be a couple minutes ahead of the slow? Need to dig in a bit..epoch_indexing_and_dataviz_layer
Tyler Goodlet
parent
530b2731ba
commit
edf721f755
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@ -853,92 +853,113 @@ async def link_views_with_region(
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hist_pi.addItem(region, ignoreBounds=True)
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region.setOpacity(6/16)
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viz = rt_chart._vizs[flume.symbol.fqsn]
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viz = rt_chart.get_viz(flume.symbol.fqsn)
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assert viz
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index_field = viz.index_field
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# XXX: no idea why this doesn't work but it's causing
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# a weird placement of the region on the way-far-left..
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# region.setClipItem(viz.graphics)
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# poll for datums load and timestep detection
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for _ in range(100):
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try:
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_, _, ratio = flume.get_ds_info()
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break
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except IndexError:
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await trio.sleep(0.01)
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continue
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if index_field == 'time':
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# in the (epoch) index case we can map directly
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# from the fast chart's x-domain values since they are
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# on the same index as the slow chart.
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def update_region_from_pi(
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window,
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viewRange: tuple[tuple, tuple],
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is_manual: bool = True,
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) -> None:
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# put linear region "in front" in layer terms
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region.setZValue(10)
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# set the region on the history chart
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# to the range currently viewed in the
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# HFT/real-time chart.
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region.setRegion(viewRange[0])
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else:
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raise RuntimeError(
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'Failed to detect sampling periods from shm!?')
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# poll for datums load and timestep detection
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for _ in range(100):
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try:
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_, _, ratio = flume.get_ds_info()
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break
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except IndexError:
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await trio.sleep(0.01)
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continue
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else:
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raise RuntimeError(
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'Failed to detect sampling periods from shm!?')
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# sampling rate transform math:
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# -----------------------------
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# define the fast chart to slow chart as a linear mapping
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# over the fast index domain `i` to the slow index domain
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# `j` as:
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#
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# j = i - i_offset
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# ------------ + j_offset
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# j/i
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#
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# conversely the inverse function is:
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#
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# i = j/i * (j - j_offset) + i_offset
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#
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# Where `j_offset` is our ``izero_hist`` and `i_offset` is our
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# `izero_rt`, the ``ShmArray`` offsets which correspond to the
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# indexes in each array where the "current" time is indexed at init.
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# AKA the index where new data is "appended to" and historical data
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# if "prepended from".
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#
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# more practically (and by default) `i` is normally an index
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# into 1s samples and `j` is an index into 60s samples (aka 1m).
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# in the below handlers ``ratio`` is the `j/i` and ``mn``/``mx``
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# are the low and high index input from the source index domain.
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# sampling rate transform math:
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# -----------------------------
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# define the fast chart to slow chart as a linear mapping
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# over the fast index domain `i` to the slow index domain
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# `j` as:
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#
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# j = i - i_offset
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# ------------ + j_offset
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# j/i
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#
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# conversely the inverse function is:
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#
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# i = j/i * (j - j_offset) + i_offset
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#
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# Where `j_offset` is our ``izero_hist`` and `i_offset` is our
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# `izero_rt`, the ``ShmArray`` offsets which correspond to the
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# indexes in each array where the "current" time is indexed at init.
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# AKA the index where new data is "appended to" and historical data
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# if "prepended from".
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#
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# more practically (and by default) `i` is normally an index
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# into 1s samples and `j` is an index into 60s samples (aka 1m).
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# in the below handlers ``ratio`` is the `j/i` and ``mn``/``mx``
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# are the low and high index input from the source index domain.
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def update_region_from_pi(
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window,
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viewRange: tuple[tuple, tuple],
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is_manual: bool = True,
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def update_region_from_pi(
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window,
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viewRange: tuple[tuple, tuple],
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is_manual: bool = True,
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) -> None:
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# put linear region "in front" in layer terms
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region.setZValue(10)
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) -> None:
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# put linear region "in front" in layer terms
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region.setZValue(10)
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# set the region on the history chart
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# to the range currently viewed in the
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# HFT/real-time chart.
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mn, mx = viewRange[0]
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ds_mn = (mn - izero_rt)/ratio
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ds_mx = (mx - izero_rt)/ratio
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lhmn = ds_mn + izero_hist
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lhmx = ds_mx + izero_hist
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# print(
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# f'rt_view_range: {(mn, mx)}\n'
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# f'ds_mn, ds_mx: {(ds_mn, ds_mx)}\n'
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# f'lhmn, lhmx: {(lhmn, lhmx)}\n'
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# )
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region.setRegion((
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lhmn,
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lhmx,
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))
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# set the region on the history chart
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# to the range currently viewed in the
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# HFT/real-time chart.
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mn, mx = viewRange[0]
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ds_mn = (mn - izero_rt)/ratio
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ds_mx = (mx - izero_rt)/ratio
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lhmn = ds_mn + izero_hist
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lhmx = ds_mx + izero_hist
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# print(
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# f'rt_view_range: {(mn, mx)}\n'
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# f'ds_mn, ds_mx: {(ds_mn, ds_mx)}\n'
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# f'lhmn, lhmx: {(lhmn, lhmx)}\n'
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# )
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region.setRegion((
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lhmn,
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lhmx,
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))
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# TODO: if we want to have the slow chart adjust range to
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# match the fast chart's selection -> results in the
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# linear region expansion never can go "outside of view".
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# hmn, hmx = hvr = hist_chart.view.state['viewRange'][0]
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# print((hmn, hmx))
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# if (
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# hvr
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# and (lhmn < hmn or lhmx > hmx)
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# ):
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# hist_pi.setXRange(
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# lhmn,
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# lhmx,
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# padding=0,
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# )
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# hist_linked.graphics_cycle()
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# TODO: if we want to have the slow chart adjust range to
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# match the fast chart's selection -> results in the
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# linear region expansion never can go "outside of view".
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# hmn, hmx = hvr = hist_chart.view.state['viewRange'][0]
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# print((hmn, hmx))
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# if (
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# hvr
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# and (lhmn < hmn or lhmx > hmx)
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# ):
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# hist_pi.setXRange(
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# lhmn,
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# lhmx,
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# padding=0,
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# )
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# hist_linked.graphics_cycle()
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# connect region to be updated on plotitem interaction.
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rt_pi.sigRangeChanged.connect(update_region_from_pi)
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@ -1333,12 +1354,11 @@ async def display_symbol_data(
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)
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godwidget.resize_all()
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# hist_chart.hide()
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# await link_views_with_region(
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# rt_chart,
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# hist_chart,
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# flume,
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# )
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await link_views_with_region(
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rt_chart,
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hist_chart,
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flume,
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)
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# start graphics update loop after receiving first live quote
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ln.start_soon(
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