Turns out this is a limitation of the `ViewBox.setYRange()` api: you
can't call it more then once and expect anything but the first call to
be applied without letting a render cycle run. As such, we wait until
the end of the log-linear scaling loop to finally apply the major curves
y-mx/mn after all minor curves have been evaluated.
This also drops all the debug prints (for now) to get a feel for latency
in production mode.
We ended up doing groups maxmin sorting at the interaction layer (new
the view box) and thus this method is no longer needed, though it was
the reference for the code now in `ChartView.interact_graphics_cycle()`.
Further this adds a `remove_axes: bool` arg to `.insert_plotitem()`
which can be used to drop axis entries from the inserted pi (though it
doesn't seem like we really ever need that?) and does the removal in
a separate loop to avoid removing axes before they are registered in
`ComposedGridLayout._pi2axes`.
When there are `N`-curves we need to consider the smallest
x-data-support subset when figuring out for each major-minor pair such
that the "shorter" series is always returns aligned to the longer one.
This makes the var naming more explicit with `major/minor_i_start` as
well as clarifies more stringently a bunch of other variables and
explicitly uses the `minor_y_intersect` y value in the scaling transform
calcs. Also fixes some debug prints.
In very close manner to the original (gut instinct) attempt, this
properly (y-axis-vertically) aligns and scales overlaid curves according
to what we are calling a "log-linearized y-range multi-plot" B)
The basic idea is that a simple returns measure (eg. `R = (p1 - p0)
/ p0`) applied to all curves gives a constant output `R` no matter the
price co-domain in use and thus gives a constant returns over all assets
in view styled scaling; a intuitive visual of returns correlation. The
reference point is for now the left-most point in view (or highest
common index available to all curves), though we can make this
a parameter based on user needs.
A slew of debug `print()`s are left in for now until we iron out the
remaining edge cases to do with re-scaling a major (dispersion) curve
based on a minor now requiring a larger log-linear y-range from that
previous major' range.
In the dispersion swing calcs, use the series median from the in-view
data to determine swing proportions to apply on each "minor curve"
(series with lesser dispersion the one with the greatest). Track the
major `Viz` as before by max dispersion. Apply the dispersion swing
proportions to each minor curve-series in a third loop/pass of all
overlay groups: this ensures all overlays are dispersion normalized in
their ranges but, minor curves are currently (vertically) centered (vs.
the major) via their medians.
There is a ton of commented code from attempts to try and vertically
align minor curves to the major via the "first datum" in-view/available.
This still needs work and we may want to offer it as optional.
Also adds logic to allow skipping margin adjustments in `._set_yrange()`
if you pass `range_margin=None`.
On overlaid ohlc vizs we compute the largest max/min spread and
apply that maxmimum "up and down swing" proportion to each `Viz`'s
viewbox in the group.
We obviously still need to clip to the shortest x-range so that
it doesn't look exactly the same as before XD
We were hacking this before using the whole `ChartView._maxmin()`
setting stuff since in some cases you might want similarly ranged paths
on the same view, but of course you need to max/min them together..
This adds that group sorting by using a table of `dict[PlotItem,
tuple[float, float]` and taking the abs highest/lowest value for each
plot in the viz interaction update loop.
Also removes the now commented signal registry calls and thus
`._yranger`, drops the `set_range: bool` from `._set_yrange` and adds
and extra `.maybe_downsample_graphics()` to the mouse wheel handler to
avoid a weird slow debounce where ds-ing is delayed until a further
interaction.
It's kind of hard to understand with the C++ fan-out to multiple views
(imo a cluster-f#$*&) and seems honestly just plain faster to loop (in
python) through all the linked view handlers XD
Core adjustments:
- make the panning and wheel-scroll handlers just call
`.maybe_downsample_graphics()` directly; drop all signal emissions.
- make `.maybe_downsample_graphics()` loop through all vizs per subchart
and use the new pipeline-style call sequence of:
- `Viz.update_graphics() -> <read_slc>: tuple`
- `Viz.maxmin(i_read_range=<read_slc>) -> yrange: tuple`
- `Viz.plot.vb._set_yrange(yrange=yrange)`
which inlines all the necessary calls in the most efficient way whilst
leveraging `.maxmin()` caching and ymxmn-from-m4-during-render to
boot.
- drop registering `._set_yrange()` for handling `.sigRangeChangedManually`.
Computes the maxmin values for each underlying plot's in-view range as
well as the max up/down swing (in percentage terms) from the plot with
most dispersion and returns a all these values plus a `dict` of plots to
their ranges as part of output.
Curve-path colouring and cache mode settings are used (and can thus be
factored out of) all child types; this moves them into the parent type's
`.__init__()` and adjusts all sub-types match:
- the bulk was moved out of the `Curve.__init__()` including all
previous commentary around cache settings.
- adjust `BarItems` to use a `NoCache` mode and instead use the
`last_step_pen: pg.Pen` and `._pen` inside it's `.pain()` instead of
defining functionally duplicate vars.
- adjust all (transitive) calls to `BarItems` to use the new kwargs
names.
Allows callers to know if they should care about a particular viz
rendering call by immediately knowing if the graphics are in view. This
turns out super useful particularly when doing dynamic y-ranging overlay
calcs.
First, we rename what was `chart_maxmin()` -> `multi_maxmin()` and don't
`partial` it in to the `DisplayState`, just call it with correct `Viz`
ref inputs.
Second, as we've done with `ChartView.maybe_downsample_graphics()` use
the output from the main `Viz.update_graphics()` and feed it to the
`.maxmin()` calls for the ohlc and vlm chart but still deliver the same
output signature as prior. Also accept and use an optional profiler
input, drop `DisplayState.maxmin()` and add `.vlm_viz`.
Further perf related tweak to do with more efficient incremental
updates:
- only call `multi_maxmin()` if the main fast chart viz does a pixel
column step.
- mask out hist viz and vlm viz and all linked fsp `._set_yrange()`
calls for now until we figure out how to best optimize these updates
when considering the new group-scaled-by-% style for multicharts.
- drop `.enable_auto_yrange()` calls during startup.
Acts as short cut when pipe-lining from `Viz.update_graphics()` (which
now returns the needed in-view array-relative-read-slice as output) such
that `Viz.read()` and `.datums_range()` doesn't need to be called
internally multiple times. In this case where `i_read_range` is provided
we of course skip doing time index translations and consequently lookup
the appropriate (epoch-time) index indices for caching.
Removes the multi-maxmin usage as well as ensures appropriate `Viz` refs
are passed into the view methods now requiring it. Also drops the "back
linking" of the vlm chart view to the source OHLC chart since we're
going to add this as a default to the charting API.
The max min for a given data range is defined on the lowest level
through the `Viz` api intermingling it with the view is a layering
issue. Instead make `._set_yrange()` call the appropriate view's viz
(since they should be one-to-one) directly and thus avoid any callback
monkey patching nonsense.
Requires that we now make `._set_yrange()` require either one of an
explicit `yrange: tuple[float, float]` min/max pair or the `Viz` ref (so
that maxmin can be called) as input. Adjust
`enable/disable_auto_yrange()` to bind in a new `._yranger()` partial
that's (solely) needed for signal reg/unreg which binds in the now
required input `Viz` to these methods.
Comment the `autoscale_overlays` block in `.maybe_downsample_graphics()`
for now until we figure out the most sane way to auto-range all linked
overlays and subplots (with their own overlays).
In an effort to ensure uniform and uppx-optimized last datum graphics
updates call this method directly instead of the equivalent graphics
object thus ensuring we only update the last pixel column according with
the appropriate max/min computed from the last uppx's worth of data.
Fixes / improvements to enable `.draw_last()` usage include,
- change `Viz._render_table` -> `._alt_r: tuple[Renderer, pg.GraphicsItem] | None`
which holds an alternative (usually downsampled) render and graphics
obj.
- extend the `.draw_last()` signature to include:
- `last_read` to allow passing in the already read data from
`.update_graphics()`, if it isn't passed then a manual read is done
internally.
- `reset_cache: bool` which is passed through to the graphics obj.
- use the new `Formatter.flat_index_ratio: float` when indexing into xy
1d data to compute the max/min for that px column.
Other,
- drop `bars_range` input from `maxmin()` since it's unused.
For the purposes of avoiding another full format call we can stash the
last rendered 1d xy pre-graphics formats as
`IncrementalFormatter.x/y_1d: np.ndarray`s and allow readers in the viz
and render machinery to use this data easily for things like "only
drawing the last uppx's worth of data as a line". Also add
a `.flat_index_ratio: float` which can be used similarly as a scalar
applied to indexes into the src array but instead when indexing
(flattened) 1d xy formatted outputs. Finally, this drops the way
overdone/noisy `.__repr__()` meth we had XD
When a new tick comes in but no new time step / bar is yet needed (to be
appended) we can simply adjust **only** the last bar datum
lines-graphic(s) to avoid a redraw of the preceding `QPainterPath` on
every tick. Do this by calling `Viz.draw_last()` on the fast and slow
chart and adjusting the guards around calls to `Viz.update_graphics()`
(which *does* update paths) to only enter when there's a `do_px_step`
condition. We can stop calling `main_viz.plot.vb._set_yrange()` on view
treading cases since the range should have already been adjusted by the
clearing-tick processing mxmn updates.
Further this changes,
- the `chart_maxmin()` helper (which we should eventually just get rid
of) to take bound in `Viz`s for the ohlc and vlm chart instead of the
chart widget handles.
- extend the guard around hist viz yranging to only enter when not in
"axis mode" - the same as for the fast viz.
Since we removed the `Viz.update_graphics()` call from the main rt loop
we have to be sure to call it in the history chart incr-loop to avoid
a gap between the last bar and prior history since startup. We only
need to update on tread since that should be the only time a full redraw
is ever necessary, ow only the last datum is needed.
Further this moves the graphics cycle func's profiler init to the top in
an effort to get more correct latency measures.
Since `ChartPlotWidget.update_graphics_from_flow()` is more or less just
a call to `Viz.update_graphics()` try to call that directly where
possible.
Changes include:
- calling the viz in the display state specific `maxmin()`.
- passing a viz instance to each `ChartView._set_yrange()` call (in prep
of explicit group auto-ranging); not that this input is unused in the
method for now.
- drop `bars_range` var passing since we don't use it.
Inside `._interaction` routines we need access to `Viz` instances.
Instead of doing `CharPlotWidget._vizs: dict` lookups this ensures each
plot can lookup it's (parent) viz without error.
Also, adjusts `Viz.maxmin()` output parsing to new signature.
Move the `Viz.datums_range()` call into `Viz.maxmin()` itself thus
minimizing the chart `.maxmin()` method to an ultra light wrapper around
the viz call. Also move all profiling into the `Viz` method.
Adjust `Viz.maxmin()` to return both the (rounded) x-range values which
correspond to the range containing the y-domain min and max so that
it can be used for up and coming overlay group maxmin calcs.
We obviously don't want to be debugging a sample-index issue if/when the
market for the asset is closed (since we'll be guaranteed to have
a mismatch, lul). Pass in the `feed_is_live: trio.Event` throughout the
backfilling routines to allow first checking for the live feed being active
so as to avoid breakpointing on false +ves. Also, add a detailed warning
log message for when *actually* investigating a mismatch.
Tyler Goodlet