Whenever the last datum is in view `slice_from_time()` need to always
spec the final array index (i.e. the len - 1 value we set as
`read_i_max`) to avoid a uniform-step arithmetic error where gaps in the
underlying time series causes an index that's too low to be returned.
- adjust zoom focal to be min of the view-right coord or the right-most
point on the flow graphic in view and drop all the legacy l1-in-view
focal point cruft.
- flip to not auto-scaling overlays by default.
- change the `._set_yrange()` margin to `0.09`.
- drop `use_vr: bool` usage.
Before this axes were being stacked from the outside in (for `'right'`
and 'bottom'` axes) which is somewhat non-intuitive for an `.append()`
operation. As such this change makes a symbol list stack a set of
`'right'` axes from left-to-right.
Details:
- rename `ComposeGridLayout.items` -> `.pitems`
- return `(int, list[AxisItem])` pairs from `.insert/append_plotitem()`
and the down stream `PlotItemOverlay.add_plotitem()`.
- drop `PlotItemOverlay.overlays` and add it back as `@property` around
the underlying `.layout.pitems`.
Factor and fix dst <- src pair parsing into a new func
`get_likely_pair()` and use throughout initial position loading; solves
a parsing bug for src asset balances which aren't only 3 chars long..
a terrible assumption.
Goes back to always adjusting the y-axis range to include the L1 spread
and clearing label in view whenever the last datum is also in view,
previously this was broken after reworking the display loop for
multi-feeds.
Drops a bunch of old commented tick looping cruft from before we started
using tick-type framing. Also adds more stringent guards for ignoring
but error logging quote values that are more then 25% out of range; it
seems particularly our `ib` feed has some issues with strange `price`
values that are way off here and there?
Instead of having the l1 lines be inside the view space, move them to be
inside their respective axis (with only a 16 unit portion inside the
view) such that the clear price label can overlay with them nicely
without obscuring; this is much better suited to multiple adjacent
y-axes and in general is simpler and less noisy.
Further `L1Labels` + `LevelLabel` style tweaks:
- adjust `.rect` positioning to be "right" (i.e. inside the parent
y-axis) with a slight 16 unit shift toward the viewbox (using the new
`._x_br_offset`) to allow seeing each level label's line even when the
clearing price label is positioned at that same level.
- add a newline's worth of vertical space to each of the bid/ask labels
so that L1 labels' text content isn't ever obscured by the clear price
label.
- set a low (10) z-value to ensure l1 labels are always placed
underneath the clear price label.
- always fill the label rect with the chosen background color.
- make labels fully opaque so as to always make them hide the parent
axes' `.tickStrings()` contents.
- make default color the "default" from the global scheme.
- drop the "price" part from the l1 label text contents, just show the
book-queue's amount (in dst asset's units, aka the potential clearing vlm).
In the case where the last-datum-graphic hasn't been created yet, simply
return a `None` from this method so the caller can choose to ignore the
output. Further, drop `.px_width()` since it makes more sense defined on
`Viz` as well as the previously commented `BarItems.x_uppx()` method.
Also, don't round the `.x_uppx()` output since it can then be used when
< 1 to do x-domain scaling during high zoom usage.
Factor some common methods into the parent type:
- `.x_uppx()` for reading the horizontal units-per-pixel.
- `.x_last()` for reading the "closest to y-axis" last datum coordinate
for zooming "around" during mouse interaction.
- `.px_width()` for computing the max width of any curve in view in
pixels.
Adjust all previous derived `pg.GraphicsObject` child types to now
inherit from this new parent and in particular enable proper `.x_uppx()`
support to `BarItems`.
Use proper uppx scaling when either of scaling the data to the x-domain
index-range or when the uppx is < 1 (now that we support it) such that
both the fast and slow chart always appropriately scale and offset to
the y-axis with the last datum graphic just adjacent to the order line
arrow markers.
Further this fixes the `.index_step()` calc to use the "earliest" 16
values to compute the expected sample step diff since the last set often
contained gaps due to start up race conditions and generated
unexpected/incorrect output.
Further this drops the `.curve_width_pxs()` method and replaces it with
`.px_width()`, taken from the graphics object API and instead returns
the pixel account for the whole view width instead of the
x-domain-data-range within the view.
Doesn't seem like we really need to handle the situation where the start
or stop input time stamps are outside the index range of the data since
the new binary search handling via `numpy.searchsorted()` covers this
case at minimal runtime cost and with an equally correct output. Allows
us to drop some other indexing endpoint internal variables as well.
We want the fast and slow chart to behave the same on calls to
`Viz.default_view()` so adjust the offset calc to make both work:
- just offset by the line len regardless of step / uppx
- add back the `should_line: bool` output from `render_bar_items()` (and
use it to set a new `ds_allowed: bool` guard variable) so that we can
bypass calling the m4 downsampler unless the bars have been switched
to the interpolation line graphic (which we normally required before
any downsampling of OHLC graphics data).
Further, this drops use of the `use_vr: bool` flag from all rendering
since we pretty much always use it by default.
Previously with array-int indexing we had to map the input x-domain
"indexes" passed to `DynamicDateAxis._indexes_to_timestr()`. In the
epoch-time indexing case we obviously don't need to lookup time stamps
from the underlying shm array and can instead just cast to `int` and
relay the values verbatim.
Further, this patch includes some style adjustments to `AxisLabel` to
better enable multi-feed chart overlays by avoiding L1 label clutter
when multiple y-axes are stacked adjacent:
- adjust the `Axis` typical max string to include a couple spaces suffix
providing for a bit more margin between side-by-side y-axes.
- make the default label (fill) color the "default" from the global
color scheme and drop it's opacity to .9
- add some new label placement options and use them in the
`.boundingRect()` method:
* `._x/y_br_offset` for relatively shifting the overall label relative
to it's parent axis.
* `._y_txt_h_scaling` for increasing the bounding rect's height
without including more whitespace in the label's text content.
- ensure labels have a high z-value such that by default they are always
placed "on top" such that when we adjust the l1 labels they can be set
to a lower value and thus never obscure the last-price label.
Turns out we were updating the wrong ``Viz``/``DisplayState`` inside the
closure style `increment_history_view()`` (probably due to looping
through the flumes and dynamically closing in that task-func).. Instead
define the history incrementer at module level and pass in the
`DisplayState` explicitly. Further rework the `DisplayState` attrs to be
more focused around the `Viz` associated with the fast and slow chart
and be sure to adjust output from each `Viz.incr_info()` call to latest
update. Oh, and just tweaked the line palette for the moment.
FYI "treading" here is referring to the x-shifting of the curve when
the last datum is in view such that on new sampled appends the "last"
datum is kept in the same x-location in UI terms.
Mainly it was the global (should we )increment logic that needs to be
independent for the fast vs. slow chart such that the slow isn't
update-shifted by the fast and vice versa. We do this using a new
`'i_last_slow'` key in the `DisplayState.globalz: dict` which is
singleton for each sample-rate-specific chart and works for both time
and array indexing.
Also, we drop some old commented `graphics.draw_last_datum()` code that
never ended up being needed again inside the coordinate cache reset
bloc.
Might as well since it makes the chart look less gappy and we can easily
flip the index switch now B)
Also adds a new `'i_slow_last'` key to `DisplayState` for a singleton
across all slow charts and thus no more need for special case logic in
`viz.incr_info()`.
Define the x-domain coords "offset" (determining the curve graphics
per-datum placement) for each formatter such that there's only on place
to change it when needed. Obviously each graphics type has it's own
dimensionality and this is reflected by the array shapes on each
subtype.
Previously we were drawing with the middle of the bar on each index with
arms to either side: +/- some arm length. Instead this changes so that
each bar is drawn *after* each index/timestamp such that in graphics
coords the bar span more correctly matches the time span in the
x-domain. This makes the linked region between slow and fast chart
directly match (without any transform) for epoch-time indexing such that
the last x-coord in view on the fast chart is no more then the
next time step in (downsampled) slow view.
Deats:
- adjust in `._pathops.path_arrays_from_ohlc()` and take an `bar_w` bar
width input (normally taken from the data step size).
- change `.ui._ohlc.bar_from_ohlc_row()` and
`BarItems.draw_last_datum()` to match.
Allows easily switching between normal array `int` indexing and time
indexing by just flipping the `Viz._index_field: str`.
Also, guard all the x-data audit breakpoints with a time indexing
condition.
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..
Using a global "last index step" (via module var) obviously has problems
when working with multiple feed sets in a single global app instance:
any separate feed-set will be incremented according to an app-global
index-step and thus won't correctly calc per-feed-set-step update info.
Impl deatz:
- drop `DisplayState.incr_info()` (since previously moved to `Viz`) and
call that method on each appropriate `Viz` instance where necessary;
further ensure the appropriate `DisplayState` instance is passed in to
each call and make sure to pass a `state: DisplayState`.
- add `DisplayState.hist_vars: dict` for history chart (sets) to
determine the per-feed (not set) current slow chart (time) step.
- add `DisplayState.globalz: dict` to house a common per-feed-set state
and use it inside the new `Viz.incr_info()` such that
a `should_increment: bool` can be returned and used by the display
loop to determine whether to x-shift the current chart.
Read the `Viz.index_step()` directly to avoid always reading 1 on the
slow chart; this was completely broken before and resulting in not
rendering the bars graphic on the slow chart until at a true uppx of
1 which obviously doesn't work for 60 width bars XD
Further cleanups to `._render` module:
- drop `array` output from `Renderer.render()`, `read_from_key` input
and fix type annot.
- drop `should_line`, `changed_to_line` and `render_kwargs` from
`render_baritems()` outputs and instead calc `should_redraw` logic
inside the func body and return as output.
First allocation vs. first "prepend" of source data to an xy `ndarray`
format **must be mutex** in order to avoid a double prepend.
Previously when both blocks were executed we'd end up with
a `.xy_nd_start` that was decremented (at least) twice as much as it
should be on the first `.format_to_1d()` call which is obviously
incorrect (and causes problems for m4 downsampling as discussed below).
Further, since the underlying `ShmArray` buffer indexing is managed
(i.e. write-updated) completely independently from the incremental
formatter updates and internal xy indexing, we can't use
`ShmArray._first.value` and instead need to use the particular `.diff()`
output's prepend length value to decrement the `.xy_nd_start` on updates
after initial alloc.
Problems this resolves with m4:
- m4 uses a x-domain diff to calculate the number of "frames" to
downsample to, this is normally based on the ratio of pixel columns on
screen vs. the size of the input xy data.
- previously using an int-index (not epoch time) the max diff between
first and last index would be the size of the input buffer and thus
would never cause a large mem allocation issue (though it may have
been inefficient in terms of needed size).
- with an epoch time index this max diff could explode if you had some
near-now epoch time stamp **minus** an x-allocation value: generally
some value in `[0.5, -0.5]` which would result in a massive frames and
thus internal `np.ndarray()` allocation causing either a crash in
`numba` code or actual system mem over allocation.
Further, put in some more x value checks that trigger breakpoints if we
detect values that caused this issue - we'll remove em after this has
been tested enough.
Turns out we can't seem to avoid the artefacts when click-drag-scrolling
(results in weird repeated "smeared" curve segments) so just go back to
the original code.
Ensures that a "last datum" graphics object exists so that zooming can
read it using `.x_last()`. Also, disable the linked region stuff for now
since it's totally borked after flipping to the time indexing.
Since we don't really need it defined on the "chart widget" move it to
a viz method and rework it to hell:
- always discard the invalid view l > r case.
- use the graphic's UPPX to determine UI-to-scene coordinate scaling for
the L1-label collision detection, if there is no L1 just offset by
a few (index step scaled) datums; this allows us to drop the 2x
x-range calls as was hacked previous.
- handle no-data-in-view cases explicitly and error if we get any
ostensibly impossible cases.
- expect caller to trigger a graphics cycle if needed.
Further support this includes a rework a slew of other important
details:
- add `Viz.index_step`, an idempotent computed, index (presumably uniform)
step value which is needed for variable sample rate graphics displayed
on an epoch (second) time index.
- rework `Viz.datums_range()` to pass view x-endpoints as first and last
elements in return `tuple`; tighten up snap-to-data edge case logic
using `max()`/`min()` calls and better internal var naming.
- adjust all calls to `slice_from_time()` to not expect an "abs" slice.
- drop all `.yrange` resetting since we can just have the `Renderer` do
it when necessary.
If we presume that time indexing using a uniform step we can calculate
the exact index (using `//`) for the input time presuming the data
set has zero gaps. This gives a massive speedup over `numpy` fancy
indexing and (naive) `numba` iteration. Further in the case where time
gaps are detected, we can use `numpy.searchsorted()` to binary search
for the nearest expected index at lower latency.
Deatz,
- comment-disable the call to the naive `numba` scan impl.
- add a optional `step: int` input (calced if not provided).
- add todos for caching binary search results in the gap detection
cases.
- drop returning the "absolute buffer indexing" slice since the caller
can always just use the read-relative slice to acquire it.
When we use an epoch index and any sample rate > 1s we need to scale the
"number of bars" to that step in order to place the view correctly in
x-domain terms. For now we're calcing the step in-method but likely,
longer run, we'll pull this from elsewhere (like a ``Viz`` attr).
Gives approx a 3-4x speedup using plain old iterate-with-for-loop style
though still not really happy with this .5 to 1 ms latency..
Move the core `@njit` part to a `_slice_from_time()` with a pure python
func with orig name around it. Also, drop the output `mask` array since
we can generally just use the slices in the caller to accomplish the
same input array slicing, duh..
We need to subtract the first index in the array segment read, not the
first index value in the time-sliced output, to get the correct offset
into the non-absolute (`ShmArray.array` read) array..
Further we **do** need the `&` between the advance indexing conditions
and this adds profiling to see that it is indeed real slow (like 20ms
ish even when using `np.where()`).
Tyler Goodlet
goodboy