Commit Graph

14 Commits (9c5bc6dedaa06c9d42346431b740628cf0e14ec8)

Author SHA1 Message Date
Tyler Goodlet 9c5bc6deda Add `.ui._pathops` module
Starts a module for grouping together all our `QPainterpath` related
generation and data format operations for creation of fast curve
graphics. To start, drops `FastAppendCurve.downsample()` and moves
it to a new `._pathops.xy_downsample()`.
2022-06-05 22:13:08 -04:00
Tyler Goodlet bc50db5925 Rename `._ohlc.gen_qpath()` -> `.gen_ohlc_qpath()` 2022-06-05 22:13:08 -04:00
Tyler Goodlet cfc4198837 Use new profiler arg name, add more marks throughout flow update 2022-06-05 22:13:08 -04:00
Tyler Goodlet fb38265199 Clean out legacy code from `Flow.update_graphics()` 2022-06-05 22:13:08 -04:00
Tyler Goodlet 36a10155bc Add profiler passthrough type annot, comments about appends vs. uppx 2022-06-05 22:13:08 -04:00
Tyler Goodlet b12921678b Drop step routine import 2022-06-05 22:13:08 -04:00
Tyler Goodlet 12d60e6d9c WIP get incremental step curve updates working
This took longer then i care to admit XD but it definitely adds a huge
speedup and with only a few outstanding correctness bugs:

- panning from left to right causes strange trailing artifacts in the
  flows fsp (vlm) sub-plot but only when some data is off-screen on the
  left but doesn't appear to be an issue if we keep the `._set_yrange()`
  handler hooked up to the `.sigXRangeChanged` signal (but we aren't
  going to because this makes panning way slower). i've got a feeling
  this is a bug todo with the device coordinate cache stuff and we may
  need to report to Qt core?
- factoring out the step curve logic from
  `FastAppendCurve.update_from_array()` (un)fortunately required some
  logic branch uncoupling but also meant we needed special input controls
  to avoid things like redraws and curve appends for special cases,
  this will hopefully all be better rectified in code when the core of
  this method is moved into a renderer type/implementation.
- the `tina_vwap` fsp curve now somehow causes hangs when doing erratic
  scrolling on downsampled graphics data. i have no idea why or how but
  disabling it makes the issue go away (ui will literally just freeze
  and gobble CPU on a `.paint()` call until you ctrl-c the hell out of
  it). my guess is that something in the logic for standard line curves
  and appends on large data sets is the issue?

Code related changes/hacks:
- drop use of `step_path_arrays_from_1d()`, it was always a bit hacky
  (being based on `pyqtgraph` internals) and was generally hard to
  understand since it returns 1d data instead of the more expected (N,2)
  array of "step levels"; instead this is now implemented (uglily) in
  the `Flow.update_graphics()` block for step curves (which will
  obviously get cleaned up and factored elsewhere).
- add a bunch of new flags to the update method on the fast append
  curve:  `draw_last: bool`, `slice_to_head: int`, `do_append: bool`,
  `should_redraw: bool` which are all controls to aid with previously
  mentioned issues specific to getting step curve updates working
  correctly.
- add a ton of commented tinkering related code (that we may end up
  using) to both the flow and append curve methods that was written as
  part of the effort to get this all working.
- implement all step curve updating inline in `Flow.update_graphics()`
  including prepend and append logic for pre-graphics incremental step
  data maintenance and in-view slicing as well as "last step" graphics
  updating.

Obviously clean up commits coming stat B)
2022-06-05 22:13:08 -04:00
Tyler Goodlet b2b31b8f84 WIP incrementally update step array format 2022-06-05 22:13:08 -04:00
Tyler Goodlet aee44fed46 Right, handle the case where the shm prepend history isn't full XD 2022-06-05 22:13:08 -04:00
Tyler Goodlet 7e1ec7b5a7 Incrementally update flattend OHLC data
After much effort (and exhaustion) but failure to get a view into our
`numpy` OHLC struct-array, this instead allocates an in-thread-memory
array which is updated with flattened data every flow update cycle.

I need to report what I think is a bug to `numpy` core about the whole
view thing not working but, more or less this gets the same behaviour
and minimizes work to flatten the sampled data for line-graphics drawing
thus improving refresh latency when drawing large downsampled curves.

Update the OHLC ds curve with view aware data sliced out from the
pre-allocated and incrementally updated data (we had to add a last index
var `._iflat` to track appends - this should be moved into a renderer
eventually?).
2022-06-05 22:13:08 -04:00
Tyler Goodlet 427a33654b More WIP, implement `BarItems` rendering in `Flow.update_graphics()` 2022-06-05 22:13:08 -04:00
Tyler Goodlet e0a72a2174 WIP starting architecture doc str writeup.. 2022-06-05 22:13:08 -04:00
Tyler Goodlet 5a9bab0b69 WIP incremental render apis 2022-06-05 22:13:08 -04:00
Tyler Goodlet c097016fd2 Add new `ui._flows` module
This begins the removal of data processing / analysis methods from the
chart widget and instead moving them to our new `Flow` API (in the new
module introduce here) and delegating the old chart methods to the
respective internal flow. Most importantly is no longer storing the
"last read" of an array from shm in an internal chart table (was
`._arrays`) and instead the `ShmArray` instance is passed as input and
stored in the `Flow` instance. This greatly simplifies lookup logic such
that the display loop now doesn't have to worry about reading shm, it
can be done by internal graphics logic as desired. Generally speaking,
all previous `._arrays`/`._graphics` lookups are now delegated to the
entries in the chart's `._flows` table.

The new `Flow` methods are generally better factored and provide more
detailed output regarding data-stream <-> graphics inter-relations for
the future purpose of allowing much more efficient update calls in the
display loop as well as supporting low latency interaction UX.

The concept here is that we're introducing an intermediary layer that
ties together graphics and real-time data flows such that widget code is
oriented around plot layout and the flow apis are oriented around
real-time low latency updates and providing an efficient high level
metric layer for the UX.

The summary api transition is something like:
- `update_graphics_from_array()` -> `.update_graphics_from_flow()`
- `.bars_range()` -> `Flow.datums_range()`
- `.bars_range()` -> `Flow.datums_range()`
2022-06-05 22:13:08 -04:00