By mapping any in view "contents labels" to the range of the
``ViewBox``'s data we can avoid having graphics overlap with labels.
Take this approach instead of specifying a min y-range using the std
and activate the range compute on resize and mouser scrolling.
Also, add y-sticky update for signal plots.
Use two separate `QPicture` instances:
- one for the 3 lines for the last bar
- one for all the historical bars lines
On price changes update the last bar and only update historical bars
when the current bar's period expires (when a new bar is "added").
Add a flag `just_history` for this `BarItems.draw_lines()`.
Also, switch the internal lines array/buffer to a 2D numpy array to avoid
the type-cast step and instead just flatten using `numpy.ravel()`.
Overall this should avoid the problem of draws getting slower over time
as new bars are added to the history since price updates only redraw
a single bar to the "last" `QPicture` instance. Ideally in the future we
can make the `history` `QPicture` a `QPixmap` but it looks like this
will require some internal work in `pyqtgraph` to support it.
Use a ``rec2array`` struct array converter to generate lines sequence
faster. Start looking into using a `QPixmap` to avoid redrawing all
bars every update.
Add a default "contents label" (eg. OHLC values for bar charts) to each
chart and update on crosshair interaction.
Few technical changes to make this happen:
- adjust bar graphics to have the HL line be in the "middle" of the
underlying arrays' "index range" in the containing view.
- add a label dict each chart's graphics name to a label + update routine
- use symbol names instead of this "main" identifier crap for referring to
particular price curves/graphics
This is a first attempt at a financial signal processing subsystem which
utilizes async generators for streaming frames of numpy array data
between actors. In this initial attempt the focus is on processing price
data and relaying it to the chart app for real-time display. So far this
seems to work (with decent latency) but much more work is likely needed
around improving the data model for even better latency and less data
duplication.
Surprisingly (or not?) a lot of simplifications to the charting code
came out of this in terms of conducting graphics updates in streaming
tasks instead of hiding them inside the obfuscated mess that is the
Qt-style-inheritance-OO-90s-trash. The goal from here on wards will be
to enforce strict semantics around reading and writing of data such that
state is kept outside "object trees" as much as possible and streaming
function semantics guide our flow model. Unsurprisingly, this reduction
in "instance state" is happening wherever we use `trio` ;)
A little summary on the technical changes:
- not going to explain the fsp system yet; it's too nascent and
probably going to get some heavy editing.
- drop any "update" methods from the `LinkedCharts` type since each
sub-chart will have it's own update task and thus a separate update
loop; further individual graphics (per chart) may eventually require
this same design.
- delete `ChartView`; moved into separate mod.
- add "stream from fsp" task to start our foray into real-time actor
processed numpy streaming.
Wait for a first actual real-time quote before starting graphics update
tasks. Use the new normalized tick format brokers are expected to emit
as a `quotes['ticks']` list. Auto detect time frame from historical
bars.
Add `ChartPlotWidget.add_plot()` to add sub charts for indicators which
can be updated independently. Clean up rt bar update code and drop some
legacy ohlc loading cruft.
Stop with all this "main chart" special treatment.
Manage all lines in the same way across all referenced plots.
Add `CrossHair.add_plot()` for adding new plots dynamically.
Just, smh.
Tyler Goodlet