For whatever reason if the `QLineF` high/low values are the same a weird
little rectangle is drawn (my guess is a `float` precision error of some
sort). Instead, if they're the same just use one of the values.
Also, store local vars to avoid so many lookups.
Infected `asyncio` support is being added to `tractor` in
goodboy/tractor#121 so delegate to all that new machinery.
Start building out an "actor-aware" api which takes care of all the
`trio`-`asyncio` interaction for data streaming and request handling.
Add a little (shudder) method proxy system which can be used to invoke
client methods from another actor. Start on a streaming api in
preparation for real-time charting.
Start working towards meeting the backend client api.
Infect `asyncio` using `trio`'s new guest mode and demonstrate
real-time ticker streaming to console.
`pg.PlotCurveItem.setData()` is normally used for real-time updates to
curves and takes in a whole new array of data to graphics.
It makes sense to stick with this interface especially if
the current datum graphic will originally be drawn from tick quotes and
later filled in when bars data is available (eg. IB has this option in
TWS charts for volume). Additionally, having a data feed api where the push
process/task can write to shared memory and the UI task(s) can read from
that space is ideal. It allows for indicator and algo calculations to be
run in parallel (via actors) with initial price draw instructions
such that plotting of downstream metrics can be "pipelined" into the
chart UI's render loop. This essentially makes the chart UI async
programmable from multiple remote processes (or at least that's the
goal).
Some details:
- Only store a single ref to the source array data on the
`LinkedSplitCharts`. There should only be one reference since the main
relation is **that** x-time aligned sequence.
- Add `LinkedSplitCharts.update_from_quote()` which takes in a quote
dict and updates the OHLC array from it's contents.
- Add `ChartPlotWidget.update_from_array()` method to trigger graphics
updates per chart with consideration for overlay curves.
This makes a OHLC graphics "sequence" update very similar (actually API
compatible) with `pg.PlotCurveItem.setData()`. The difference here is
that only latest OHLC datum is used to update the charts last bar.
This was a mess before with a weird loop using the parent split charts
to update all "indicators". Instead just have each plot do its own
yrange updates since the signals are being handled just fine per plot.
Handle both the OHLC and plane line chart cases with a hacky `try:,
except IndexError:` for now.
Oh, and move the main entry point for the chart app to the relevant
module. I added some WIP bar update code for the moment.
Speed up the lines array creation using proper slice assignment.
This gives another 10% speedup to the historical price rendering.
Drop ``_tina_mode`` support for now since we're not testing it.
Previously graphics were loaded and rendered implicitly during the
import and creation of certain objects. Remove all this and instead
expect client code to pass in the OHLC sequence to plot. Speed up
the bars graphics rendering by simplifying to a single iteration of
the input array; gives about a 2x speedup.
Move chart resize code into our ``ViewBox`` subtype (a ``ChartView``)
in an effort to start organizing interaction behaviour closer to the
appropriate underlying objects. Add some docs for all this and do some
renaming.
Modify the default ``ViewBox`` scroll to zoom behaviour such that
whatever right-most point is visible is used as the "center" for
zooming. Add a "traditional" cross-hair cursor.
- Move out equity plotting to new module.
- Make axis margins and fonts look good on i3.
- Adjust axis labels colors to gray.
- Start commenting a lot of the code after figuring out what it all does
when cross referencing with ``pyqtgraph``.
- Add option to move date axis to middle.
Hand select necessary components to get real-time charting with
`pyqtgraph` from the `Quantdom` projects:
https://github.com/constverum/Quantdom
We've offered to collaborate with the author but have received no
response and the project has not been updated in over a year.
Given this, we are moving forward with taking the required components to
make further improvements upon especially since the `pyqtgraph` project
is now being actively maintained again.
If the author comes back we will be more then happy to contribute
modified components upstream:
https://github.com/constverum/Quantdom/issues/18
Relates to #80
This is something I've been meaning to try for a while and will likely
make writing tick data to a db more straight forward (filling in NaN
values is more matter of fact) plus it should minimize bandwidth usage.
Note, it'll require stream consumers to be considerate of non-full
quotes arriving and thus using the first "full" quote message to fill
out dynamically formatted systems or displays.
Tyler Goodlet