piker/piker/ui/_display.py

1652 lines
51 KiB
Python

# piker: trading gear for hackers
# Copyright (C) Tyler Goodlet (in stewardship for pikers)
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
real-time display tasks for charting graphics update.
this module ties together quote and computational (fsp) streams with
graphics update methods via our custom ``pyqtgraph`` charting api.
'''
import itertools
from math import floor
import time
from typing import (
Any,
TYPE_CHECKING,
)
import tractor
import trio
import pyqtgraph as pg
# import pendulum
from msgspec import field
# from .. import brokers
from piker.accounting import (
MktPair,
)
from piker.types import Struct
from piker.data import (
open_feed,
Feed,
Flume,
open_sample_stream,
ShmArray,
)
from piker.data.ticktools import (
_tick_groups,
_auction_ticks,
)
from piker.toolz import (
pg_profile_enabled,
ms_slower_then,
Profiler,
)
from piker.log import get_logger
from piker import config
# from ..data._source import tf_in_1s
from ._axes import YAxisLabel
from ._chart import (
ChartPlotWidget,
LinkedSplits,
GodWidget,
)
from ._dataviz import Viz
from ._l1 import L1Labels
from ._style import hcolor
from ._fsp import (
update_fsp_chart,
start_fsp_displays,
open_vlm_displays,
)
from ._forms import (
FieldsForm,
mk_order_pane_layout,
)
from . import _pg_overrides as pgo
from .order_mode import (
open_order_mode,
OrderMode,
)
if TYPE_CHECKING:
from ._interaction import ChartView
log = get_logger(__name__)
# TODO: delegate this to each `Viz.maxmin()` which includes
# caching and further we should implement the following stream based
# approach, likely with ``numba``:
# https://arxiv.org/abs/cs/0610046
# https://github.com/lemire/pythonmaxmin
def multi_maxmin(
i_read_range: tuple[int, int] | None,
fast_viz: Viz,
vlm_viz: Viz | None = None,
profiler: Profiler = None,
) -> tuple[
tuple[int, int, int, int],
float,
float,
float,
]:
'''
Compute max and min datums "in view" for range limits.
'''
out = fast_viz.maxmin(
i_read_range=i_read_range,
)
if out is None:
# log.warning(f'No yrange provided for {name}!?')
return (0, 0, 0)
(
ixrng,
read_slc,
yrange,
) = out
if profiler:
profiler(f'fast_viz.maxmin({read_slc})')
mn, mx = yrange
# TODO: we need to NOT call this to avoid a manual
# np.max/min trigger and especially on the vlm_chart
# vizs which aren't shown.. like vlm?
mx_vlm_in_view = 0
if vlm_viz:
out = vlm_viz.maxmin(
i_read_range=i_read_range,
)
if out:
(
ixrng,
read_slc,
mxmn,
) = out
mx_vlm_in_view = mxmn[1]
if profiler:
profiler(f'vlm_viz.maxmin({read_slc})')
return (
# enforcing price can't be negative?
# TODO: do we even need this?
max(mn, 0),
mx,
mx_vlm_in_view, # vlm max
)
class DisplayState(Struct):
'''
Chart-local real-time graphics state container.
'''
fqme: str
godwidget: GodWidget
quotes: dict[str, Any]
flume: Flume
# high level chart handles and underlying ``Viz``
chart: ChartPlotWidget
viz: Viz
hist_chart: ChartPlotWidget
hist_viz: Viz
# axis labels
l1: L1Labels
last_price_sticky: YAxisLabel
hist_last_price_sticky: YAxisLabel
vlm_viz: Viz
# misc state tracking
vars: dict[str, Any] = field(
default_factory=lambda: {
'i_last': 0,
'i_last_append': 0,
'last_mx_vlm': 0,
}
)
hist_vars: dict[str, Any] = field(
default_factory=lambda: {
'i_last': 0,
'i_last_append': 0,
'last_mx_vlm': 0,
}
)
globalz: None | dict[str, Any] = None
vlm_chart: ChartPlotWidget | None = None
vlm_sticky: YAxisLabel | None = None
async def increment_history_view(
# min_istream: tractor.MsgStream,
ds: DisplayState,
):
hist_chart: ChartPlotWidget = ds.hist_chart
hist_viz: Viz = ds.hist_viz
# viz: Viz = ds.viz
assert 'hist' in hist_viz.shm.token['shm_name']
# name: str = hist_viz.name
# TODO: seems this is more reliable at keeping the slow
# chart incremented in view more correctly?
# - It might make sense to just inline this logic with the
# main display task? => it's a tradeoff of slower task
# wakeups/ctx switches verus logic checks (as normal)
# - we need increment logic that only does the view shift
# call when the uppx permits/needs it
# draw everything from scratch on first entry!
for curve_name, hist_viz in hist_chart._vizs.items():
log.info(f'Forcing hard redraw -> {curve_name}')
hist_viz.reset_graphics()
# hist_viz.update_graphics(force_redraw=True)
async with open_sample_stream(1.) as min_istream:
async for msg in min_istream:
profiler = Profiler(
msg=f'History chart cycle for: `{ds.fqme}`',
delayed=True,
disabled=not pg_profile_enabled(),
ms_threshold=ms_slower_then,
# ms_threshold=4,
)
# NOTE: when a backfill msg is broadcast from the
# history mgmt layer, we match against the equivalent
# `Viz` and "hard re-render" (i.e. re-allocate the
# in-mem xy-array formats managed in
# `.data._formatters) its curve graphics to fill
# on-chart gaps.
# TODO: specifically emit/handle range tuples?
# - samplerd could emit the actual update range via
# tuple and then we only enter the below block if that
# range is detected as in-view?
# match msg:
# case {
# 'backfilling': (viz_name, timeframe),
# } if (
# viz_name == name
# ):
# log.warning(
# f'Forcing HARD REDRAW:\n'
# f'name: {name}\n'
# f'timeframe: {timeframe}\n'
# )
# # TODO: only allow this when the data is IN VIEW!
# # also, we probably can do this more efficiently
# # / smarter by only redrawing the portion of the
# # path necessary?
# {
# 60: hist_viz,
# 1: viz,
# }[timeframe].update_graphics(
# force_redraw=True
# )
# check if slow chart needs an x-domain shift and/or
# y-range resize.
(
uppx,
liv,
do_px_step,
i_diff_t,
append_diff,
do_rt_update,
should_tread,
) = hist_viz.incr_info(
ds=ds,
is_1m=True,
)
if do_px_step:
hist_viz.update_graphics()
profiler('`hist Viz.update_graphics()` call')
if liv:
hist_viz.plot.vb.interact_graphics_cycle(
do_linked_charts=False,
do_overlay_scaling=True, # always overlayT slow chart
)
profiler('hist chart yrange view')
# check if tread-in-place view x-shift is needed
if should_tread:
# ensure path graphics append is shown on treads since
# the main rt loop does not call this.
hist_chart.increment_view(datums=append_diff)
profiler('hist tread view')
profiler.finish()
async def graphics_update_loop(
dss: dict[str, DisplayState],
nurse: trio.Nursery,
godwidget: GodWidget,
feed: Feed,
# min_istream: tractor.MsgStream,
pis: dict[str, list[pgo.PlotItem, pgo.PlotItem]] = {},
vlm_charts: dict[str, ChartPlotWidget] = {},
) -> None:
'''
The 'main' (price) chart real-time update loop.
Receive from the primary instrument quote stream and update the OHLC
chart.
'''
# TODO: bunch of stuff (some might be done already, can't member):
# - I'm starting to think all this logic should be
# done in one place and "graphics update routines"
# should not be doing any length checking and array diffing.
# - handle odd lot orders
# - update last open price correctly instead
# of copying it from last bar's close
# - 1-5 sec bar lookback-autocorrection like tws does?
# (would require a background history checker task)
linked: LinkedSplits = godwidget.rt_linked
display_rate = godwidget.window.current_screen().refreshRate()
fast_chart = linked.chart
hist_chart = godwidget.hist_linked.chart
assert hist_chart
# per-viz-set global last index tracking for global chart
# view UX incrementing; these values are singleton
# per-multichart-set such that automatic x-domain shifts are only
# done once per time step update.
globalz = {
'i_last_t': 0, # multiview-global fast (1s) step index
'i_last_slow_t': 0, # multiview-global slow (1m) step index
}
for fqme, flume in feed.flumes.items():
ohlcv = flume.rt_shm
hist_ohlcv = flume.hist_shm
mkt = flume.mkt
fqme = mkt.fqme
# update last price sticky
fast_viz = fast_chart._vizs[fqme]
index_field = fast_viz.index_field
fast_pi = fast_viz.plot
last_price_sticky = fast_pi.getAxis('right')._stickies[fqme]
last_price_sticky.update_from_data(
*ohlcv.array[-1][[
index_field,
'close',
]]
)
last_price_sticky.show()
hist_viz = hist_chart._vizs[fqme]
slow_pi = hist_viz.plot
hist_last_price_sticky = slow_pi.getAxis('right')._stickies[fqme]
hist_last_price_sticky.update_from_data(
*hist_ohlcv.array[-1][[
index_field,
'close',
]]
)
vlm_chart = vlm_charts[fqme]
vlm_viz = vlm_chart._vizs.get('volume') if vlm_chart else None
(
last_mn,
last_mx,
last_mx_vlm,
) = multi_maxmin(
None,
fast_viz,
vlm_viz,
)
last, volume = ohlcv.array[-1][['close', 'volume']]
mkt = flume.mkt
l1 = L1Labels(
fast_pi,
# determine precision/decimal lengths
digits=mkt.price_tick_digits,
size_digits=mkt.size_tick_digits,
)
# TODO:
# - in theory we should be able to read buffer data faster
# then msgs arrive.. needs some tinkering and testing
# - if trade volume jumps above / below prior L1 price
# levels this might be dark volume we need to
# present differently -> likely dark vlm
fast_chart.show()
last_quote_s = time.time()
dss[fqme] = ds = linked.display_state = DisplayState(**{
'fqme': fqme,
'godwidget': godwidget,
'quotes': {},
'flume': flume,
'chart': fast_chart,
'viz': fast_viz,
'last_price_sticky': last_price_sticky,
'hist_chart': hist_chart,
'hist_viz': hist_viz,
'hist_last_price_sticky': hist_last_price_sticky,
'vlm_viz': vlm_viz,
'l1': l1,
'vars': {
'i_last': 0,
'i_last_append': 0,
'last_mx_vlm': last_mx_vlm,
# 'last_mx': last_mx,
# 'last_mn': last_mn,
},
'globalz': globalz,
})
if vlm_chart:
vlm_pi = vlm_viz.plot
vlm_sticky = vlm_pi.getAxis('right')._stickies['volume']
ds.vlm_chart = vlm_chart
ds.vlm_sticky = vlm_sticky
fast_chart.main_viz.default_view(
do_min_bars=True,
)
# ds.hist_vars.update({
# 'i_last_append': 0,
# 'i_last': 0,
# })
nurse.start_soon(
increment_history_view,
# min_istream,
ds,
)
await trio.sleep(0)
if ds.hist_vars['i_last'] < ds.hist_vars['i_last_append']:
await tractor.pause()
# try:
# XXX TODO: we need to do _dss UPDATE here so that when
# a feed-view is switched you can still remote annotate the
# prior view..
from . import _remote_ctl
_remote_ctl._dss.update(dss)
# main real-time quotes update loop
stream: tractor.MsgStream
async with feed.open_multi_stream() as stream:
# assert stream
async for quotes in stream:
quote_period = time.time() - last_quote_s
quote_rate = round(
1/quote_period, 1) if quote_period > 0 else float('inf')
if (
quote_period <= 1/_quote_throttle_rate
# in the absolute worst case we shouldn't see more then
# twice the expected throttle rate right!?
# and quote_rate >= _quote_throttle_rate * 2
and quote_rate >= display_rate
):
pass
# log.warning(f'High quote rate {mkt.fqme}: {quote_rate}')
last_quote_s: float = time.time()
for fqme, quote in quotes.items():
ds = dss[fqme]
ds.quotes = quote
rt_pi, hist_pi = pis[fqme]
# chart isn't active/shown so skip render cycle and
# pause feed(s)
if (
fast_chart.linked.isHidden()
or not rt_pi.isVisible()
):
print(f'{fqme} skipping update for HIDDEN CHART')
fast_chart.pause_all_feeds()
continue
ic = fast_chart.view._in_interact
if ic:
fast_chart.pause_all_feeds()
print(f'{fqme} PAUSING DURING INTERACTION')
await ic.wait()
fast_chart.resume_all_feeds()
# sync call to update all graphics/UX components.
graphics_update_cycle(
ds,
quote,
)
# finally:
# # XXX: cancel any remote annotation control ctxs
# _remote_ctl._dss = None
# for cid, (ctx, aids) in _remote_ctl._ctxs.items():
# await ctx.cancel()
def graphics_update_cycle(
ds: DisplayState,
quote: dict,
trigger_all: bool = False, # flag used by prepend history updates
prepend_update_index: int | None = None,
# NOTE: this has to be manually turned on in code (or by
# caller) to get profiling since by default we never want the
# overhead!
debug_n_trace: bool = False,
) -> None:
if debug_n_trace:
profiler = Profiler(
msg=f'Graphics loop cycle for: `{ds.fqme}`',
disabled=not pg_profile_enabled(),
ms_threshold=ms_slower_then,
delayed=True,
# ms_threshold=4,
)
# TODO: SPEEDing this all up..
# - optimize this whole graphics stack with ``numba`` hopefully
# or at least a little `mypyc` B)
# - pass more direct refs as input to avoid so many attr accesses?
# - use a streaming minmax algo and drop the use of the
# state-tracking ``multi_maxmin()`` routine from above?
fqme = ds.fqme
chart = ds.chart
vlm_chart = ds.vlm_chart
# varz = ds.vars
l1 = ds.l1
flume = ds.flume
ohlcv = flume.rt_shm
array = ohlcv.array
hist_viz = ds.hist_viz
main_viz = ds.viz
index_field = main_viz.index_field
(
uppx,
liv,
do_px_step,
i_diff_t,
append_diff,
do_rt_update,
should_tread,
) = main_viz.incr_info(ds=ds)
if debug_n_trace:
profiler('`.incr_info()`')
# TODO: we should only run mxmn when we know
# an update is due via ``do_px_step`` above.
# TODO: eventually we want to separate out the dark vlm and show
# them as an additional graphic.
clear_types = _tick_groups['clears']
# TODO: fancier y-range sorting..
# https://github.com/pikers/piker/issues/325
# - a proper streaming mxmn algo as per above issue.
# - we should probably scale the view margin based on the size of
# the true range? This way you can slap in orders outside the
# current L1 (only) book range.
main_vb: ChartView = main_viz.plot.vb
this_viz: Viz = chart._vizs[fqme]
this_vb: ChartView = this_viz.plot.vb
this_yr = this_vb._yrange
if this_yr:
lmn, lmx = this_yr
else:
lmn = lmx = 0
mn: float = lmn
mx: float = lmx
mx_vlm_in_view: float | None = None
yrange_margin = 0.09
# update ohlc sampled price bars
if (
(liv and do_px_step)
or trigger_all
):
# TODO: i think we're double calling this right now
# since .interact_graphics_cycle() also calls it?
# I guess we can add a guard in there?
_, i_read_range, _ = main_viz.update_graphics()
if debug_n_trace:
profiler('`Viz.update_graphics()` call')
# don't real-time "shift" the curve to the
# left unless we get one of the following:
if (
should_tread
or trigger_all
):
chart.increment_view(datums=append_diff)
# NOTE: since vlm and ohlc charts are axis linked now we don't
# need the double increment request?
# if vlm_chart:
# vlm_chart.increment_view(datums=append_diff)
if debug_n_trace:
profiler('view incremented')
# NOTE: do this **after** the tread to ensure we take the yrange
# from the most current view x-domain.
(
mn,
mx,
mx_vlm_in_view,
) = multi_maxmin(
i_read_range,
main_viz,
ds.vlm_viz,
profiler if debug_n_trace else None,
)
if debug_n_trace:
profiler(f'{fqme} `multi_maxmin()` call')
# iterate frames of ticks-by-type such that we only update graphics
# using the last update per type where possible.
ticks_by_type = quote.get('tbt', {})
for typ, ticks in ticks_by_type.items():
if typ not in _auction_ticks:
if debug_n_trace:
log.warning(
'Skipping non-auction-native `{typ}` ticks:\n'
f'{ticks}\n'
)
continue
# NOTE: ticks are `.append()`-ed to the `ticks_by_type: dict` by the
# `._sampling.uniform_rate_send()` loop
tick = ticks[-1] # get most recent value
price = tick.get('price')
size = tick.get('size')
# compute max and min prices (including bid/ask) from
# tick frames to determine the y-range for chart
# auto-scaling.
if (
liv
# TODO: make sure IB doesn't send ``-1``!
and price > 0
):
if (
price < mn
):
if debug_n_trace:
log.info(f'{this_viz.name} new MN from TICK {mn} -> {price}')
mn = price
yrange_margin = 0.16
if (
price > mx
):
if debug_n_trace:
log.info(f'{this_viz.name} new MX from TICK {mx} -> {price}')
mx = price
yrange_margin = 0.16
# mx = max(price, mx)
# mn = min(price, mn)
# clearing price update:
# generally, we only want to update grahpics from the *last*
# tick event once - thus showing the most recent state.
if typ in clear_types:
# update price sticky(s)
end_ic = array[-1][[
index_field,
'close',
]]
ds.last_price_sticky.update_from_data(*end_ic)
ds.hist_last_price_sticky.update_from_data(*end_ic)
# update OHLC chart last bars
# TODO: fix the only last uppx stuff....
main_viz.draw_last() # only_last_uppx=True)
hist_viz.draw_last() # only_last_uppx=True)
# L1 book label-line updates
if typ in ('last',):
label = {
l1.ask_label.fields['level']: l1.ask_label,
l1.bid_label.fields['level']: l1.bid_label,
}.get(price)
if (
label is not None
and liv
):
label.update_fields(
{'level': price, 'size': size}
)
# TODO: on trades should we be knocking down
# the relevant L1 queue manually ourselves?
# label.size -= size
# NOTE: right now we always update the y-axis labels
# despite the last datum not being in view. Ideally
# we have a guard for this when we detect that the range
# of those values is not in view and then we disable these
# blocks.
elif (
typ in _tick_groups['asks']
):
l1.ask_label.update_fields({'level': price, 'size': size})
elif (
typ in _tick_groups['bids']
):
l1.bid_label.update_fields({'level': price, 'size': size})
if debug_n_trace:
profiler('L1 labels updates')
# Y-autoranging: adjust y-axis limits based on state tracking
# of previous "last" L1 values which are in view.
mn_diff = mn - lmn
mx_diff = mx - lmx
if (
mn_diff or mx_diff # covers all cases below?
# (mx - lmx) > 0 # upward expansion
# or (mn - lmn) < 0 # downward expansion
# or (lmx - mx) > 0 # upward contraction
# or (lmn - mn) < 0 # downward contraction
):
# complain about out-of-range outliers which can show up
# in certain annoying feeds (like ib)..
if (
lmx
and lmn
and (
abs(mx_diff) > .25 * lmx
or
abs(mn_diff) > .25 * lmn
)
and debug_n_trace
):
log.error(
f'WTF MN/MX IS WAY OFF:\n'
f'lmn: {lmn}\n'
f'mn: {mn}\n'
f'lmx: {lmx}\n'
f'mx: {mx}\n'
f'mx_diff: {mx_diff}\n'
f'mn_diff: {mn_diff}\n'
)
chart.pause_all_feeds()
breakpoint()
chart.resume_all_feeds()
# TODO: track local liv maxmin without doing a recompute all the
# time..plus, just generally the user is more likely to be
# zoomed out enough on the slow chart that this is never an
# issue (the last datum going out of y-range).
# FAST CHART y-auto-range resize case
elif (
liv
and not chart._static_yrange == 'axis'
):
# NOTE: this auto-yranging approach is a sort of, hybrid,
# between always aligning overlays to the their common ref
# sample and not updating at all:
# - whenever an interaction happens the overlays are scaled
# to one another and thus are ref-point aligned and
# scaled.
# - on treads and range updates due to new mn/mx from last
# datum, we don't scale to the overlayT instead only
# adjusting when the latest datum is outside the previous
# dispersion range.
mn = min(mn, lmn)
mx = max(mx, lmx)
if (
main_vb._in_interact is None
or not main_vb._in_interact.is_set()
):
# print(f'SETTING Y-mnmx -> {main_viz.name}: {(mn, mx)}')
this_vb.interact_graphics_cycle(
do_linked_charts=False,
# TODO: we could optionally offer always doing this
# on treads thus always keeping fast-chart overlays
# aligned by their LHS datum?
do_overlay_scaling=False,
yrange_kwargs={
this_viz: {
'yrange': (mn, mx),
'range_margin': yrange_margin,
},
}
)
if debug_n_trace:
profiler('main vb y-autorange')
# SLOW CHART y-auto-range resize casd
# (NOTE: still is still inside the y-range
# guard block above!)
# (
# _,
# hist_liv,
# _,
# _,
# _,
# _,
# _,
# ) = hist_viz.incr_info(
# ds=ds,
# is_1m=True,
# )
# if hist_liv:
# times = hist_viz.shm.array['time']
# last_t = times[-1]
# dt = pendulum.from_timestamp(last_t)
# log.info(
# f'{hist_viz.name} TIMESTEP:'
# f'epoch: {last_t}\n'
# f'datetime: {dt}\n'
# )
# if debug_n_trace:
# profiler('hist `Viz.incr_info()`')
# hist_chart = ds.hist_chart
# if (
# hist_liv
# and not hist_chart._static_yrange == 'axis'
# ):
# hist_viz.plot.vb._set_yrange(
# viz=hist_viz,
# # yrange=yr, # this is the rt range, not hist.. XD
# )
# profiler('hist vb y-autorange')
# XXX: update this every draw cycle to ensure y-axis auto-ranging
# only adjusts when the in-view data co-domain actually expands or
# contracts.
# varz['last_mn'] = mn
# varz['last_mx'] = mx
# TODO: a similar, only-update-full-path-on-px-step approach for all
# fsp overlays and vlm stuff..
# run synchronous update on all `Viz` overlays
for curve_name, viz in chart._vizs.items():
if viz.is_ohlc:
continue
# update any overlayed fsp flows
if (
curve_name != fqme
):
update_fsp_chart(
viz,
curve_name,
array_key=curve_name,
)
# even if we're downsampled bigly
# draw the last datum in the final
# px column to give the user the mx/mn
# range of that set.
if (
liv
# and not do_px_step
# and not do_rt_update
):
viz.draw_last(
array_key=curve_name,
# TODO: XXX this is currently broken for the
# `FlattenedOHLC` case since we aren't returning the
# full x/y uppx's worth of src-data from
# `draw_last_datum()` ..
only_last_uppx=True,
)
if debug_n_trace:
profiler('overlays updates')
# volume chart logic..
# TODO: can we unify this with the above loop?
if vlm_chart:
vlm_vizs = vlm_chart._vizs
main_vlm_viz = vlm_vizs['volume']
main_vlm_vb = main_vlm_viz.plot.vb
# TODO: we should probably read this
# from the `Viz.vs: ViewState`!
vlm_yr = main_vlm_vb._yrange
if vlm_yr:
(_, vlm_ymx) = vlm_yrange = vlm_yr
# always update y-label
ds.vlm_sticky.update_from_data(
*array[-1][[
index_field,
'volume',
]]
)
if (
(
do_rt_update
or do_px_step
and liv
)
or trigger_all
):
# TODO: make it so this doesn't have to be called
# once the $vlm is up?
main_vlm_viz.update_graphics(
# UGGGh, see ``maxmin()`` impl in `._fsp` for
# the overlayed plotitems... we need a better
# bay to invoke a maxmin per overlay..
render=False,
# XXX: ^^^^ THIS IS SUPER IMPORTANT! ^^^^
# without this, since we disable the
# 'volume' (units) chart after the $vlm starts
# up we need to be sure to enable this
# auto-ranging otherwise there will be no handler
# connected to update accompanying overlay
# graphics..
)
if debug_n_trace:
profiler('`main_vlm_viz.update_graphics()`')
if (
mx_vlm_in_view
and vlm_yr
and mx_vlm_in_view != vlm_ymx
):
# in this case we want to scale all overlays in the
# sub-chart but only incrementally update the vlm since
# we already calculated the new range above.
# TODO: in theory we can incrementally update all
# overlays as well though it will require iteration of
# them here in the display loop right?
main_vlm_viz.plot.vb.interact_graphics_cycle(
do_overlay_scaling=True,
do_linked_charts=False,
yrange_kwargs={
main_vlm_viz: {
'yrange': vlm_yrange,
# 'range_margin': yrange_margin,
},
},
)
if debug_n_trace:
profiler('`vlm_chart.view.interact_graphics_cycle()`')
# update all downstream FSPs
for curve_name, viz in vlm_vizs.items():
if curve_name == 'volume':
continue
if (
viz.render
and (
liv and do_rt_update
or do_px_step
)
and curve_name not in {fqme}
):
update_fsp_chart(
viz,
curve_name,
array_key=curve_name,
)
if debug_n_trace:
profiler(f'vlm `Viz[{viz.name}].update_graphics()`')
# is this even doing anything?
# (pretty sure it's the real-time
# resizing from last quote?)
# XXX: without this we get completely
# mangled/empty vlm display subchart..
# fvb = viz.plot.vb
# fvb.interact_graphics_cycle(
# do_linked_charts=False,
# do_overlay_scaling=False,
# )
if debug_n_trace:
profiler(
f'Viz[{viz.name}].plot.vb.interact_graphics_cycle()`'
)
# even if we're downsampled bigly
# draw the last datum in the final
# px column to give the user the mx/mn
# range of that set.
elif (
not do_px_step
and liv
and uppx >= 1
):
# always update the last datum-element
# graphic for all vizs
viz.draw_last(array_key=curve_name)
if debug_n_trace:
profiler(f'vlm `Viz[{viz.name}].draw_last()`')
if debug_n_trace:
profiler('vlm Viz all updates complete')
if debug_n_trace:
profiler.finish()
async def link_views_with_region(
rt_chart: ChartPlotWidget,
hist_chart: ChartPlotWidget,
flume: Flume,
) -> None:
# these value are be only pulled once during shm init/startup
izero_hist = flume.izero_hist
izero_rt = flume.izero_rt
# Add the LinearRegionItem to the ViewBox, but tell the ViewBox
# to exclude this item when doing auto-range calculations.
rt_pi = rt_chart.plotItem
hist_pi = hist_chart.plotItem
region = pg.LinearRegionItem(
movable=False,
# color scheme that matches sidepane styling
pen=pg.mkPen(hcolor('gunmetal')),
brush=pg.mkBrush(hcolor('default_darkest')),
)
region.setOpacity(0)
hist_pi.addItem(region, ignoreBounds=True)
region.setOpacity(6/16)
viz = rt_chart.get_viz(flume.mkt.fqme)
assert viz
index_field = viz.index_field
# XXX: no idea why this doesn't work but it's causing
# a weird placement of the region on the way-far-left..
# region.setClipItem(viz.graphics)
if index_field == 'time':
# in the (epoch) index case we can map directly
# from the fast chart's x-domain values since they are
# on the same index as the slow chart.
def update_region_from_pi(
window,
viewRange: tuple[tuple, tuple],
is_manual: bool = True,
) -> None:
# put linear region "in front" in layer terms
region.setZValue(10)
# set the region on the history chart
# to the range currently viewed in the
# HFT/real-time chart.
rng = mn, mx = viewRange[0]
# hist_viz = hist_chart.get_viz(flume.mkt.fqme)
# hist = hist_viz.shm.array[-3:]
# print(
# f'mn: {mn}\n'
# f'mx: {mx}\n'
# f'slow last 3 epochs: {list(hist["time"])}\n'
# f'slow last 3: {hist}\n'
# )
region.setRegion(rng)
else:
# poll for datums load and timestep detection
for _ in range(100):
try:
_, _, ratio = flume.get_ds_info()
break
except IndexError:
await trio.sleep(0.01)
continue
else:
raise RuntimeError(
'Failed to detect sampling periods from shm!?')
# sampling rate transform math:
# -----------------------------
# define the fast chart to slow chart as a linear mapping
# over the fast index domain `i` to the slow index domain
# `j` as:
#
# j = i - i_offset
# ------------ + j_offset
# j/i
#
# conversely the inverse function is:
#
# i = j/i * (j - j_offset) + i_offset
#
# Where `j_offset` is our ``izero_hist`` and `i_offset` is our
# `izero_rt`, the ``ShmArray`` offsets which correspond to the
# indexes in each array where the "current" time is indexed at init.
# AKA the index where new data is "appended to" and historical data
# if "prepended from".
#
# more practically (and by default) `i` is normally an index
# into 1s samples and `j` is an index into 60s samples (aka 1m).
# in the below handlers ``ratio`` is the `j/i` and ``mn``/``mx``
# are the low and high index input from the source index domain.
def update_region_from_pi(
window,
viewRange: tuple[tuple, tuple],
is_manual: bool = True,
) -> None:
# put linear region "in front" in layer terms
region.setZValue(10)
# set the region on the history chart
# to the range currently viewed in the
# HFT/real-time chart.
mn, mx = viewRange[0]
ds_mn = (mn - izero_rt)/ratio
ds_mx = (mx - izero_rt)/ratio
lhmn = ds_mn + izero_hist
lhmx = ds_mx + izero_hist
# print(
# f'rt_view_range: {(mn, mx)}\n'
# f'ds_mn, ds_mx: {(ds_mn, ds_mx)}\n'
# f'lhmn, lhmx: {(lhmn, lhmx)}\n'
# )
region.setRegion((
lhmn,
lhmx,
))
# TODO: if we want to have the slow chart adjust range to
# match the fast chart's selection -> results in the
# linear region expansion never can go "outside of view".
# hmn, hmx = hvr = hist_chart.view.state['viewRange'][0]
# print((hmn, hmx))
# if (
# hvr
# and (lhmn < hmn or lhmx > hmx)
# ):
# hist_pi.setXRange(
# lhmn,
# lhmx,
# padding=0,
# )
# hist_linked.graphics_cycle()
# connect region to be updated on plotitem interaction.
rt_pi.sigRangeChanged.connect(update_region_from_pi)
def update_pi_from_region():
region.setZValue(10)
mn, mx = region.getRegion()
# print(f'region_x: {(mn, mx)}')
rt_pi.setXRange(
((mn - izero_hist) * ratio) + izero_rt,
((mx - izero_hist) * ratio) + izero_rt,
padding=0,
)
# TODO BUG XXX: seems to cause a real perf hit and a recursion error
# (but used to work before generalizing for 1s ohlc offset?)..
# something to do with the label callback handlers?
# region.sigRegionChanged.connect(update_pi_from_region)
# region.sigRegionChangeFinished.connect(update_pi_from_region)
# NOTE: default is set to 60 FPS until the runtime delivers the
# discoverd hw value below.
_quote_throttle_rate: int = 60 - 6
async def display_symbol_data(
godwidget: GodWidget,
fqmes: list[str],
loglevel: str,
order_mode_started: trio.Event,
) -> None:
'''
Spawn a real-time updated chart for ``symbol``.
Spawned ``LinkedSplits`` chart widgets can remain up but hidden so
that multiple symbols can be viewed and switched between extremely
fast from a cached watch-list.
'''
# sbar = godwidget.window.status_bar
# historical data fetch
# brokermod = brokers.get_brokermod(provider)
# ohlc_status_done = sbar.open_status(
# 'retreiving OHLC history.. ',
# clear_on_next=True,
# group_key=loading_sym_key,
# )
# for fqme in fqmes:
# loading_sym_key = sbar.open_status(
# f'loading {fqme} ->',
# group_key=True
# )
# (TODO: make this not so shit XD)
# close group status once a symbol feed fully loads to view.
# sbar._status_groups[loading_sym_key][1]()
# TODO: ctl over update loop's maximum frequency.
# - load this from a config.toml!
# - allow dyanmic configuration from chart UI?
(
conf,
path,
) = config.load()
ui_conf: dict = conf['ui']
global _quote_throttle_rate
from ._window import main_window
display_rate: int = floor(
main_window().current_screen().refreshRate()
) - 6
mx_redraw_rate: int = ui_conf.get(
'max_redraw_rate',
_quote_throttle_rate,
)
if mx_redraw_rate < display_rate:
log.info(
'Down-throttling redraw rate to config setting\n'
f'display FPS: {display_rate}\n'
'max_redraw_rate: {max_redraw_rate}\n'
)
else:
_quote_throttle_rate = display_rate
# TODO: we should be able to increase this if we use some
# `mypyc` speedups elsewhere? 22ish seems to be the sweet
# spot for single-feed chart.
num_of_feeds = len(fqmes)
# if num_of_feeds > 1:
# there will be more ctx switches with more than 1 feed so we
# max throttle down a bit more.
mx_per_feed: int = (
ui_conf.get(
'per_feed_redraw_rate',
mx_redraw_rate,
)
or 16
)
# limit to at least display's FPS
# avoiding needless Qt-in-guest-mode context switches
cycles_per_feed = min(
round(_quote_throttle_rate/num_of_feeds),
mx_per_feed,
)
feed: Feed
async with (
# open_sample_stream(1.) as min_istream,
open_feed(
fqmes,
loglevel=loglevel,
tick_throttle=cycles_per_feed,
) as feed,
):
# use expanded contract symbols passed back from feed layer.
fqmes = list(feed.flumes.keys())
# step_size_s = 1
# tf_key = tf_in_1s[step_size_s]
godwidget.window.setWindowTitle(
f'{fqmes} '
# f'tick:{mkt.tick_size} '
# f'step:{tf_key} '
)
# generate order mode side-pane UI
# A ``FieldsForm`` form to configure order entry
# and add as next-to-y-axis singleton pane
pp_pane: FieldsForm = mk_order_pane_layout(godwidget)
godwidget.pp_pane = pp_pane
# create top history view chart above the "main rt chart".
rt_linked: LinkedSplits = godwidget.rt_linked
hist_linked: LinkedSplits = godwidget.hist_linked
# NOTE: here we insert the slow-history chart set into
# the fast chart's splitter -> so it's a splitter of charts
# inside the first widget slot of a splitter of charts XD
rt_linked.splitter.insertWidget(0, hist_linked)
rt_chart: None | ChartPlotWidget = None
hist_chart: None | ChartPlotWidget = None
vlm_chart: None | ChartPlotWidget = None
# TODO: I think some palette's based on asset group types
# would be good, for eg:
# - underlying and opts contracts
# - index and underlyings + futures
# - gradient in "lightness" based on liquidity, or lifetime in derivs?
palette = itertools.cycle([
# curve color, last bar curve color
['grayest', 'i3'],
['default_dark', 'default'],
['grayer', 'bracket'],
['i3', 'gray'],
])
pis: dict[str, list[pgo.PlotItem, pgo.PlotItem]] = {}
# load in ohlc data to a common linked but split chart set.
fitems: list[
tuple[str, Flume]
] = list(feed.flumes.items())
# use array int-indexing when no aggregate feed overlays are
# loaded.
if len(fitems) == 1:
from ._dataviz import Viz
Viz._index_field = 'index'
# for the "first"/selected symbol we create new chart widgets
# and sub-charts for FSPs
fqme, flume = fitems[0]
# TODO NOTE: THIS CONTROLS WHAT SYMBOL IS USED FOR ORDER MODE
# SUBMISSIONS, we need to make this switch based on selection.
rt_linked.set_mkt_info(flume.mkt)
hist_linked.set_mkt_info(flume.mkt)
ohlcv: ShmArray = flume.rt_shm
hist_ohlcv: ShmArray = flume.hist_shm
mkt: MktPair = flume.mkt
fqme: str = mkt.fqme
hist_chart = hist_linked.plot_ohlc_main(
mkt,
hist_ohlcv,
flume,
# in the case of history chart we explicitly set `False`
# to avoid internal pane creation.
# sidepane=False,
sidepane=godwidget.search,
draw_kwargs={
'last_step_color': 'original',
},
)
# ensure the last datum graphic is generated
# for zoom-interaction purposes.
hist_viz = hist_chart.get_viz(fqme)
hist_viz.draw_last(array_key=fqme)
pis.setdefault(fqme, [None, None])[1] = hist_chart.plotItem
# don't show when not focussed
hist_linked.cursor.always_show_xlabel = False
rt_chart = rt_linked.plot_ohlc_main(
mkt,
ohlcv,
flume,
# in the case of history chart we explicitly set `False`
# to avoid internal pane creation.
sidepane=pp_pane,
draw_kwargs={
'last_step_color': 'original',
},
)
rt_viz = rt_chart.get_viz(fqme)
pis.setdefault(fqme, [None, None])[0] = rt_chart.plotItem
# for pause/resume on mouse interaction
rt_chart.feed = feed
async with trio.open_nursery() as ln:
# if available load volume related built-in display(s)
vlm_charts: dict[
str,
None | ChartPlotWidget
] = {}.fromkeys(feed.flumes)
if (
flume.has_vlm()
and vlm_chart is None
):
vlm_chart = vlm_charts[fqme] = await ln.start(
open_vlm_displays,
rt_linked,
flume,
)
# load (user's) FSP set (otherwise known as "indicators")
# from an input config.
ln.start_soon(
start_fsp_displays,
rt_linked,
flume,
# loading_sym_key,
loglevel,
)
godwidget.resize_all()
await trio.sleep(0)
for fqme, flume in fitems[1:]:
# get a new color from the palette
bg_chart_color, bg_last_bar_color = next(palette)
ohlcv: ShmArray = flume.rt_shm
hist_ohlcv: ShmArray = flume.hist_shm
mkt = flume.mkt
fqme = mkt.fqme
hist_pi = hist_chart.overlay_plotitem(
name=fqme,
axis_title=flume.mkt.pair(),
)
hist_viz = hist_chart.draw_curve(
fqme,
hist_ohlcv,
flume,
array_key=fqme,
overlay=hist_pi,
pi=hist_pi,
is_ohlc=True,
color=bg_chart_color,
last_step_color=bg_last_bar_color,
)
# ensure the last datum graphic is generated
# for zoom-interaction purposes.
hist_viz.draw_last(array_key=fqme)
# TODO: we need a better API to do this..
# specially store ref to shm for lookup in display loop
# since only a placeholder of `None` is entered in
# ``.draw_curve()``.
hist_viz = hist_chart._vizs[fqme]
assert hist_viz.plot is hist_pi
pis.setdefault(fqme, [None, None])[1] = hist_pi
rt_pi = rt_chart.overlay_plotitem(
name=fqme,
axis_title=flume.mkt.pair(),
)
rt_viz = rt_chart.draw_curve(
fqme,
ohlcv,
flume,
array_key=fqme,
overlay=rt_pi,
pi=rt_pi,
is_ohlc=True,
color=bg_chart_color,
last_step_color=bg_last_bar_color,
)
# TODO: we need a better API to do this..
# specially store ref to shm for lookup in display loop
# since only a placeholder of `None` is entered in
# ``.draw_curve()``.
rt_viz = rt_chart._vizs[fqme]
assert rt_viz.plot is rt_pi
pis.setdefault(fqme, [None, None])[0] = rt_pi
rt_chart.setFocus()
# NOTE: we must immediately tell Qt to show the OHLC chart
# to avoid a race where the subplots get added/shown to
# the linked set *before* the main price chart!
rt_linked.show()
rt_linked.focus()
await trio.sleep(0)
# XXX: if we wanted it at the bottom?
# rt_linked.splitter.addWidget(hist_linked)
# greedily do a view range default and pane resizing
# on startup before loading the order-mode machinery.
for fqme, flume in feed.flumes.items():
# size view to data prior to order mode init
rt_chart.main_viz.default_view(
do_min_bars=True,
)
rt_linked.graphics_cycle()
# TODO: look into this because not sure why it was
# commented out / we ever needed it XD
# NOTE: we pop the volume chart from the subplots set so
# that it isn't double rendered in the display loop
# above since we do a maxmin calc on the volume data to
# determine if auto-range adjustements should be made.
# rt_linked.subplots.pop('volume', None)
hist_chart.main_viz.default_view(
do_min_bars=True,
do_ds=False,
)
hist_linked.graphics_cycle()
godwidget.resize_all()
await trio.sleep(0)
await link_views_with_region(
rt_chart,
hist_chart,
flume,
)
# start update loop task
dss: dict[str, DisplayState] = {}
ln.start_soon(
graphics_update_loop,
dss,
ln,
godwidget,
feed,
# min_istream,
pis,
vlm_charts,
)
# boot order-mode
order_ctl_fqme: str = fqmes[0]
mode: OrderMode
async with (
open_order_mode(
feed,
godwidget,
order_ctl_fqme,
order_mode_started,
loglevel=loglevel
) as mode,
# TODO: maybe have these startup sooner before
# order mode fully boots? but we gotta,
# -[ ] decouple the order mode bindings until
# the mode has fully booted..
# -[ ] maybe do an Event to sync?
# start input handling for ``ChartView`` input
# (i.e. kb + mouse handling loops)
rt_chart.view.open_async_input_handler(
dss=dss,
),
hist_chart.view.open_async_input_handler(
dss=dss,
),
):
rt_linked.mode = mode
rt_viz = rt_chart.get_viz(order_ctl_fqme)
rt_viz.plot.setFocus()
# default view adjuments and sidepane alignment
# as final default UX touch.
rt_chart.main_viz.default_view(
do_min_bars=True,
)
await trio.sleep(0)
hist_chart.main_viz.default_view(
do_min_bars=True,
)
hist_viz = hist_chart.get_viz(fqme)
await trio.sleep(0)
godwidget.resize_all()
await trio.sleep_forever() # let the app run.. bby