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9bc7de0cb3
...
b7f7296f3a
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@ -1791,7 +1791,7 @@ async def _setup_quote_stream(
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to_trio.send_nowait(None)
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async with load_aio_clients() as accts2clients:
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caccount_name, client = get_preferred_data_client(accts2clients)
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client = get_preferred_data_client(accts2clients)
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contract = contract or (await client.find_contract(symbol))
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ticker: Ticker = client.ib.reqMktData(contract, ','.join(opts))
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@ -33,7 +33,7 @@ ohlc_fields = [
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('high', float),
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('low', float),
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('close', float),
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('volume', float),
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('volume', int),
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('bar_wap', float),
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]
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@ -230,8 +230,8 @@ _ohlcv_dt = [
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# ohlcv sampling
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('Open', 'f4'),
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('High', 'f4'),
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('Low', 'f4'),
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('Close', 'f4'),
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('Low', 'i8'),
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('Close', 'i8'),
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('Volume', 'f4'),
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]
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@ -547,17 +547,6 @@ class Storage:
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if err:
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raise MarketStoreError(err)
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# XXX: currently the only way to do this is through the CLI:
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# sudo ./marketstore connect --dir ~/.config/piker/data
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# >> \show mnq.globex.20220617.ib/1Sec/OHLCV 2022-05-15
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# and this seems to block and use up mem..
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# >> \trim mnq.globex.20220617.ib/1Sec/OHLCV 2022-05-15
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# relevant source code for this is here:
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# https://github.com/alpacahq/marketstore/blob/master/cmd/connect/session/trim.go#L14
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# def delete_range(self, start_dt, end_dt) -> None:
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# ...
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@acm
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async def open_storage_client(
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@ -34,11 +34,10 @@ from PyQt5.QtCore import (
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from .._profile import pg_profile_enabled, ms_slower_then
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from ._style import hcolor
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# from ._compression import (
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# # ohlc_to_m4_line,
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# ds_m4,
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# )
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from ._pathops import xy_downsample
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from ._compression import (
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# ohlc_to_m4_line,
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ds_m4,
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)
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from ..log import get_logger
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@ -175,6 +174,32 @@ class FastAppendCurve(pg.GraphicsObject):
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QLineF(lbar, 0, rbar, 0)
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).length()
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def downsample(
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self,
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x,
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y,
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px_width,
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uppx,
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) -> tuple[np.ndarray, np.ndarray]:
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# downsample whenever more then 1 pixels per datum can be shown.
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# always refresh data bounds until we get diffing
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# working properly, see above..
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bins, x, y = ds_m4(
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x,
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y,
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px_width=px_width,
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uppx=uppx,
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# log_scale=bool(uppx)
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)
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x = np.broadcast_to(x[:, None], y.shape)
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# x = (x + np.array([-0.43, 0, 0, 0.43])).flatten()
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x = (x + np.array([-0.5, 0, 0, 0.5])).flatten()
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y = y.flatten()
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return x, y
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def update_from_array(
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self,
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@ -371,8 +396,7 @@ class FastAppendCurve(pg.GraphicsObject):
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self._in_ds = False
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elif should_ds and uppx and px_width > 1:
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x_out, y_out = xy_downsample(
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x_out, y_out = self.downsample(
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x_out,
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y_out,
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px_width,
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@ -437,7 +461,7 @@ class FastAppendCurve(pg.GraphicsObject):
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)
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# if should_ds:
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# new_x, new_y = xy_downsample(
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# new_x, new_y = self.downsample(
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# new_x,
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# new_y,
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# px_width,
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|
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@ -48,18 +48,19 @@ from ..data._sharedmem import (
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)
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from .._profile import (
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pg_profile_enabled,
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# ms_slower_then,
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)
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from ._pathops import (
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gen_ohlc_qpath,
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ohlc_to_line,
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to_step_format,
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ms_slower_then,
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)
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from ._ohlc import (
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BarItems,
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gen_qpath,
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)
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from ._curve import (
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FastAppendCurve,
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# step_path_arrays_from_1d,
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)
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from ._compression import (
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# ohlc_flatten,
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ds_m4,
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)
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from ..log import get_logger
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@ -113,241 +114,32 @@ def rowarr_to_path(
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)
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def render_baritems(
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flow: Flow,
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graphics: BarItems,
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read: tuple[
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int, int, np.ndarray,
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int, int, np.ndarray,
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],
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profiler: pg.debug.Profiler,
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**kwargs,
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def mk_ohlc_flat_copy(
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ohlc_shm: ShmArray,
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) -> None:
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# XXX: we bind this in currently..
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# x_basis: np.ndarray,
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# vr: Optional[slice] = None,
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) -> tuple[np.ndarray, np.ndarray]:
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'''
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Graphics management logic for a ``BarItems`` object.
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Mostly just logic to determine when and how to downsample an OHLC
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lines curve into a flattened line graphic and when to display one
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graphic or the other.
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TODO: this should likely be moved into some kind of better abstraction
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layer, if not a `Renderer` then something just above it?
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Return flattened-non-copy view into an OHLC shm array.
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'''
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(
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xfirst, xlast, array,
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ivl, ivr, in_view,
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) = read
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ohlc = ohlc_shm._array[['open', 'high', 'low', 'close']]
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# if vr:
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# ohlc = ohlc[vr]
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# x = x_basis[vr]
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# if no source data renderer exists create one.
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self = flow
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r = self._src_r
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if not r:
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# OHLC bars path renderer
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r = self._src_r = Renderer(
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flow=self,
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# TODO: rename this to something with ohlc
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draw_path=gen_ohlc_qpath,
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last_read=read,
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unstructured = rfn.structured_to_unstructured(
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ohlc,
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copy=False,
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)
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ds_curve_r = Renderer(
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flow=self,
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# just swap in the flat view
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# data_t=lambda array: self.gy.array,
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last_read=read,
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draw_path=partial(
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rowarr_to_path,
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x_basis=None,
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),
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)
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curve = FastAppendCurve(
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name='OHLC',
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color=graphics._color,
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)
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curve.hide()
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self.plot.addItem(curve)
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# baseline "line" downsampled OHLC curve that should
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# kick on only when we reach a certain uppx threshold.
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self._render_table[0] = (
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ds_curve_r,
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curve,
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)
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dsc_r, curve = self._render_table[0]
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# do checks for whether or not we require downsampling:
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# - if we're **not** downsampling then we simply want to
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# render the bars graphics curve and update..
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# - if insteam we are in a downsamplig state then we to
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x_gt = 6
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uppx = curve.x_uppx()
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in_line = should_line = curve.isVisible()
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if (
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should_line
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and uppx < x_gt
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):
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print('FLIPPING TO BARS')
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should_line = False
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elif (
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not should_line
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and uppx >= x_gt
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):
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print('FLIPPING TO LINE')
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should_line = True
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profiler(f'ds logic complete line={should_line}')
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# do graphics updates
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if should_line:
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fields = ['open', 'high', 'low', 'close']
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if self.gy is None:
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# create a flattened view onto the OHLC array
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# which can be read as a line-style format
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shm = self.shm
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(
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self._iflat_first,
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self._iflat_last,
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self.gx,
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self.gy,
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) = ohlc_to_line(
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shm,
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fields=fields,
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)
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# print(f'unstruct diff: {time.time() - start}')
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gy = self.gy
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# update flatted ohlc copy
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(
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iflat_first,
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iflat,
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ishm_last,
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ishm_first,
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) = (
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self._iflat_first,
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self._iflat_last,
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self.shm._last.value,
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self.shm._first.value
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)
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# check for shm prepend updates since last read.
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if iflat_first != ishm_first:
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# write newly prepended data to flattened copy
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gy[
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ishm_first:iflat_first
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] = rfn.structured_to_unstructured(
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self.shm._array[fields][ishm_first:iflat_first]
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)
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self._iflat_first = ishm_first
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to_update = rfn.structured_to_unstructured(
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self.shm._array[iflat:ishm_last][fields]
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)
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gy[iflat:ishm_last][:] = to_update
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profiler('updated ustruct OHLC data')
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# slice out up-to-last step contents
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y_flat = gy[ishm_first:ishm_last]
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x_flat = self.gx[ishm_first:ishm_last]
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# update local last-index tracking
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self._iflat_last = ishm_last
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# reshape to 1d for graphics rendering
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y = y_flat.reshape(-1)
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x = x_flat.reshape(-1)
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profiler('flattened ustruct OHLC data')
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# do all the same for only in-view data
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y_iv_flat = y_flat[ivl:ivr]
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x_iv_flat = x_flat[ivl:ivr]
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y_iv = y_iv_flat.reshape(-1)
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x_iv = x_iv_flat.reshape(-1)
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profiler('flattened ustruct in-view OHLC data')
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# pass into curve graphics processing
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curve.update_from_array(
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x,
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y,
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x_iv=x_iv,
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y_iv=y_iv,
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view_range=(ivl, ivr), # hack
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profiler=profiler,
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# should_redraw=False,
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# NOTE: already passed through by display loop?
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# do_append=uppx < 16,
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**kwargs,
|
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)
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curve.show()
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profiler('updated ds curve')
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else:
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# render incremental or in-view update
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# and apply ouput (path) to graphics.
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path, last = r.render(
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read,
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only_in_view=True,
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)
|
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graphics.path = path
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graphics.draw_last(last)
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|
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# NOTE: on appends we used to have to flip the coords
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# cache thought it doesn't seem to be required any more?
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# graphics.setCacheMode(QtWidgets.QGraphicsItem.NoCache)
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# graphics.setCacheMode(QtWidgets.QGraphicsItem.DeviceCoordinateCache)
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|
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# graphics.prepareGeometryChange()
|
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graphics.update()
|
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|
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if (
|
||||
not in_line
|
||||
and should_line
|
||||
):
|
||||
# change to line graphic
|
||||
|
||||
log.info(
|
||||
f'downsampling to line graphic {self.name}'
|
||||
)
|
||||
graphics.hide()
|
||||
# graphics.update()
|
||||
curve.show()
|
||||
curve.update()
|
||||
|
||||
elif in_line and not should_line:
|
||||
log.info(f'showing bars graphic {self.name}')
|
||||
curve.hide()
|
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graphics.show()
|
||||
graphics.update()
|
||||
|
||||
# update our pre-downsample-ready data and then pass that
|
||||
# new data the downsampler algo for incremental update.
|
||||
|
||||
# graphics.update_from_array(
|
||||
# array,
|
||||
# in_view,
|
||||
# view_range=(ivl, ivr) if use_vr else None,
|
||||
|
||||
# **kwargs,
|
||||
# )
|
||||
|
||||
# generate and apply path to graphics obj
|
||||
# graphics.path, last = r.render(
|
||||
# read,
|
||||
# only_in_view=True,
|
||||
# )
|
||||
# graphics.draw_last(last)
|
||||
# breakpoint()
|
||||
y = unstructured.flatten()
|
||||
# x = x_basis[:y.size]
|
||||
return y
|
||||
|
||||
|
||||
class Flow(msgspec.Struct): # , frozen=True):
|
||||
|
|
@ -565,30 +357,271 @@ class Flow(msgspec.Struct): # , frozen=True):
|
|||
|
||||
graphics = self.graphics
|
||||
if isinstance(graphics, BarItems):
|
||||
render_baritems(
|
||||
self,
|
||||
graphics,
|
||||
read,
|
||||
profiler,
|
||||
|
||||
# if no source data renderer exists create one.
|
||||
r = self._src_r
|
||||
if not r:
|
||||
# OHLC bars path renderer
|
||||
r = self._src_r = Renderer(
|
||||
flow=self,
|
||||
# TODO: rename this to something with ohlc
|
||||
draw_path=gen_qpath,
|
||||
last_read=read,
|
||||
)
|
||||
|
||||
ds_curve_r = Renderer(
|
||||
flow=self,
|
||||
|
||||
# just swap in the flat view
|
||||
# data_t=lambda array: self.gy.array,
|
||||
last_read=read,
|
||||
draw_path=partial(
|
||||
rowarr_to_path,
|
||||
x_basis=None,
|
||||
),
|
||||
|
||||
)
|
||||
curve = FastAppendCurve(
|
||||
name='OHLC',
|
||||
color=graphics._color,
|
||||
)
|
||||
curve.hide()
|
||||
self.plot.addItem(curve)
|
||||
|
||||
# baseline "line" downsampled OHLC curve that should
|
||||
# kick on only when we reach a certain uppx threshold.
|
||||
self._render_table[0] = (
|
||||
ds_curve_r,
|
||||
curve,
|
||||
)
|
||||
|
||||
dsc_r, curve = self._render_table[0]
|
||||
|
||||
# do checks for whether or not we require downsampling:
|
||||
# - if we're **not** downsampling then we simply want to
|
||||
# render the bars graphics curve and update..
|
||||
# - if insteam we are in a downsamplig state then we to
|
||||
x_gt = 6
|
||||
uppx = curve.x_uppx()
|
||||
in_line = should_line = curve.isVisible()
|
||||
if (
|
||||
should_line
|
||||
and uppx < x_gt
|
||||
):
|
||||
print('FLIPPING TO BARS')
|
||||
should_line = False
|
||||
|
||||
elif (
|
||||
not should_line
|
||||
and uppx >= x_gt
|
||||
):
|
||||
print('FLIPPING TO LINE')
|
||||
should_line = True
|
||||
|
||||
profiler(f'ds logic complete line={should_line}')
|
||||
|
||||
# do graphics updates
|
||||
if should_line:
|
||||
|
||||
fields = ['open', 'high', 'low', 'close']
|
||||
if self.gy is None:
|
||||
# create a flattened view onto the OHLC array
|
||||
# which can be read as a line-style format
|
||||
shm = self.shm
|
||||
|
||||
# flat = self.gy = self.shm.unstruct_view(fields)
|
||||
self.gy = self.shm.ustruct(fields)
|
||||
first = self._iflat_first = self.shm._first.value
|
||||
last = self._iflat_last = self.shm._last.value
|
||||
|
||||
# write pushed data to flattened copy
|
||||
self.gy[first:last] = rfn.structured_to_unstructured(
|
||||
self.shm.array[fields]
|
||||
)
|
||||
|
||||
# generate an flat-interpolated x-domain
|
||||
self.gx = (
|
||||
np.broadcast_to(
|
||||
shm._array['index'][:, None],
|
||||
(
|
||||
shm._array.size,
|
||||
# 4, # only ohlc
|
||||
self.gy.shape[1],
|
||||
),
|
||||
) + np.array([-0.5, 0, 0, 0.5])
|
||||
)
|
||||
assert self.gy.any()
|
||||
|
||||
# print(f'unstruct diff: {time.time() - start}')
|
||||
# profiler('read unstr view bars to line')
|
||||
# start = self.gy._first.value
|
||||
# update flatted ohlc copy
|
||||
(
|
||||
iflat_first,
|
||||
iflat,
|
||||
ishm_last,
|
||||
ishm_first,
|
||||
) = (
|
||||
self._iflat_first,
|
||||
self._iflat_last,
|
||||
self.shm._last.value,
|
||||
self.shm._first.value
|
||||
)
|
||||
|
||||
# check for shm prepend updates since last read.
|
||||
if iflat_first != ishm_first:
|
||||
|
||||
# write newly prepended data to flattened copy
|
||||
self.gy[
|
||||
ishm_first:iflat_first
|
||||
] = rfn.structured_to_unstructured(
|
||||
self.shm._array[fields][ishm_first:iflat_first]
|
||||
)
|
||||
self._iflat_first = ishm_first
|
||||
|
||||
# # flat = self.gy = self.shm.unstruct_view(fields)
|
||||
# self.gy = self.shm.ustruct(fields)
|
||||
# # self._iflat_last = self.shm._last.value
|
||||
|
||||
# # self._iflat_first = self.shm._first.value
|
||||
# # do an update for the most recent prepend
|
||||
# # index
|
||||
# iflat = ishm_first
|
||||
|
||||
to_update = rfn.structured_to_unstructured(
|
||||
self.shm._array[iflat:ishm_last][fields]
|
||||
)
|
||||
|
||||
self.gy[iflat:ishm_last][:] = to_update
|
||||
profiler('updated ustruct OHLC data')
|
||||
|
||||
# slice out up-to-last step contents
|
||||
y_flat = self.gy[ishm_first:ishm_last]
|
||||
x_flat = self.gx[ishm_first:ishm_last]
|
||||
|
||||
# update local last-index tracking
|
||||
self._iflat_last = ishm_last
|
||||
|
||||
# reshape to 1d for graphics rendering
|
||||
y = y_flat.reshape(-1)
|
||||
x = x_flat.reshape(-1)
|
||||
profiler('flattened ustruct OHLC data')
|
||||
|
||||
# do all the same for only in-view data
|
||||
y_iv_flat = y_flat[ivl:ivr]
|
||||
x_iv_flat = x_flat[ivl:ivr]
|
||||
y_iv = y_iv_flat.reshape(-1)
|
||||
x_iv = x_iv_flat.reshape(-1)
|
||||
profiler('flattened ustruct in-view OHLC data')
|
||||
|
||||
# legacy full-recompute-everytime method
|
||||
# x, y = ohlc_flatten(array)
|
||||
# x_iv, y_iv = ohlc_flatten(in_view)
|
||||
# profiler('flattened OHLC data')
|
||||
|
||||
curve.update_from_array(
|
||||
x,
|
||||
y,
|
||||
x_iv=x_iv,
|
||||
y_iv=y_iv,
|
||||
view_range=(ivl, ivr), # hack
|
||||
profiler=profiler,
|
||||
# should_redraw=False,
|
||||
|
||||
# NOTE: already passed through by display loop?
|
||||
# do_append=uppx < 16,
|
||||
**kwargs,
|
||||
)
|
||||
curve.show()
|
||||
profiler('updated ds curve')
|
||||
|
||||
else:
|
||||
# render incremental or in-view update
|
||||
# and apply ouput (path) to graphics.
|
||||
path, last = r.render(
|
||||
read,
|
||||
only_in_view=True,
|
||||
)
|
||||
|
||||
graphics.path = path
|
||||
graphics.draw_last(last)
|
||||
|
||||
# NOTE: on appends we used to have to flip the coords
|
||||
# cache thought it doesn't seem to be required any more?
|
||||
# graphics.setCacheMode(QtWidgets.QGraphicsItem.NoCache)
|
||||
# graphics.setCacheMode(QtWidgets.QGraphicsItem.DeviceCoordinateCache)
|
||||
|
||||
# graphics.prepareGeometryChange()
|
||||
graphics.update()
|
||||
|
||||
if (
|
||||
not in_line
|
||||
and should_line
|
||||
):
|
||||
# change to line graphic
|
||||
|
||||
log.info(
|
||||
f'downsampling to line graphic {self.name}'
|
||||
)
|
||||
graphics.hide()
|
||||
# graphics.update()
|
||||
curve.show()
|
||||
curve.update()
|
||||
|
||||
elif in_line and not should_line:
|
||||
log.info(f'showing bars graphic {self.name}')
|
||||
curve.hide()
|
||||
graphics.show()
|
||||
graphics.update()
|
||||
|
||||
# update our pre-downsample-ready data and then pass that
|
||||
# new data the downsampler algo for incremental update.
|
||||
|
||||
# graphics.update_from_array(
|
||||
# array,
|
||||
# in_view,
|
||||
# view_range=(ivl, ivr) if use_vr else None,
|
||||
|
||||
# **kwargs,
|
||||
# )
|
||||
|
||||
# generate and apply path to graphics obj
|
||||
# graphics.path, last = r.render(
|
||||
# read,
|
||||
# only_in_view=True,
|
||||
# )
|
||||
# graphics.draw_last(last)
|
||||
|
||||
else:
|
||||
# ``FastAppendCurve`` case:
|
||||
array_key = array_key or self.name
|
||||
uppx = graphics.x_uppx()
|
||||
profiler(f'read uppx {uppx}')
|
||||
profiler('read uppx')
|
||||
|
||||
if graphics._step_mode and self.gy is None:
|
||||
self._iflat_first = self.shm._first.value
|
||||
|
||||
# create a flattened view onto the OHLC array
|
||||
# which can be read as a line-style format
|
||||
shm = self.shm
|
||||
(
|
||||
self._iflat_first,
|
||||
self.gx,
|
||||
self.gy,
|
||||
) = to_step_format(
|
||||
shm,
|
||||
array_key,
|
||||
)
|
||||
|
||||
# fields = ['index', array_key]
|
||||
i = shm._array['index'].copy()
|
||||
out = shm._array[array_key].copy()
|
||||
|
||||
self.gx = np.broadcast_to(
|
||||
i[:, None],
|
||||
(i.size, 2),
|
||||
) + np.array([-0.5, 0.5])
|
||||
|
||||
# self.gy = np.broadcast_to(
|
||||
# out[:, None], (out.size, 2),
|
||||
# )
|
||||
self.gy = np.empty((len(out), 2), dtype=out.dtype)
|
||||
self.gy[:] = out[:, np.newaxis]
|
||||
|
||||
# start y at origin level
|
||||
self.gy[0, 0] = 0
|
||||
profiler('generated step mode data')
|
||||
|
||||
if graphics._step_mode:
|
||||
|
|
@ -751,11 +784,42 @@ class Flow(msgspec.Struct): # , frozen=True):
|
|||
profiler=profiler,
|
||||
**kwargs
|
||||
)
|
||||
profiler('`graphics.update_from_array()` complete')
|
||||
profiler(f'`graphics.update_from_array()` complete')
|
||||
|
||||
return graphics
|
||||
|
||||
|
||||
def xy_downsample(
|
||||
x,
|
||||
y,
|
||||
px_width,
|
||||
uppx,
|
||||
|
||||
x_spacer: float = 0.5,
|
||||
|
||||
) -> tuple[np.ndarray, np.ndarray]:
|
||||
|
||||
# downsample whenever more then 1 pixels per datum can be shown.
|
||||
# always refresh data bounds until we get diffing
|
||||
# working properly, see above..
|
||||
bins, x, y = ds_m4(
|
||||
x,
|
||||
y,
|
||||
px_width=px_width,
|
||||
uppx=uppx,
|
||||
log_scale=bool(uppx)
|
||||
)
|
||||
|
||||
# flatten output to 1d arrays suitable for path-graphics generation.
|
||||
x = np.broadcast_to(x[:, None], y.shape)
|
||||
x = (x + np.array(
|
||||
[-x_spacer, 0, 0, x_spacer]
|
||||
)).flatten()
|
||||
y = y.flatten()
|
||||
|
||||
return x, y
|
||||
|
||||
|
||||
class Renderer(msgspec.Struct):
|
||||
|
||||
flow: Flow
|
||||
|
|
|
|||
|
|
@ -25,15 +25,17 @@ from typing import (
|
|||
|
||||
import numpy as np
|
||||
import pyqtgraph as pg
|
||||
from numba import njit, float64, int64 # , optional
|
||||
from PyQt5 import QtCore, QtGui, QtWidgets
|
||||
from PyQt5.QtCore import QLineF, QPointF
|
||||
# from numba import types as ntypes
|
||||
# from ..data._source import numba_ohlc_dtype
|
||||
|
||||
from .._profile import pg_profile_enabled, ms_slower_then
|
||||
from ._style import hcolor
|
||||
from ..log import get_logger
|
||||
from ._curve import FastAppendCurve
|
||||
from ._compression import ohlc_flatten
|
||||
from ._pathops import gen_ohlc_qpath
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from ._chart import LinkedSplits
|
||||
|
|
@ -82,6 +84,119 @@ def bar_from_ohlc_row(
|
|||
return [hl, o, c]
|
||||
|
||||
|
||||
@njit(
|
||||
# TODO: for now need to construct this manually for readonly arrays, see
|
||||
# https://github.com/numba/numba/issues/4511
|
||||
# ntypes.tuple((float64[:], float64[:], float64[:]))(
|
||||
# numba_ohlc_dtype[::1], # contiguous
|
||||
# int64,
|
||||
# optional(float64),
|
||||
# ),
|
||||
nogil=True
|
||||
)
|
||||
def path_arrays_from_ohlc(
|
||||
data: np.ndarray,
|
||||
start: int64,
|
||||
bar_gap: float64 = 0.43,
|
||||
|
||||
) -> np.ndarray:
|
||||
'''
|
||||
Generate an array of lines objects from input ohlc data.
|
||||
|
||||
'''
|
||||
size = int(data.shape[0] * 6)
|
||||
|
||||
x = np.zeros(
|
||||
# data,
|
||||
shape=size,
|
||||
dtype=float64,
|
||||
)
|
||||
y, c = x.copy(), x.copy()
|
||||
|
||||
# TODO: report bug for assert @
|
||||
# /home/goodboy/repos/piker/env/lib/python3.8/site-packages/numba/core/typing/builtins.py:991
|
||||
for i, q in enumerate(data[start:], start):
|
||||
|
||||
# TODO: ask numba why this doesn't work..
|
||||
# open, high, low, close, index = q[
|
||||
# ['open', 'high', 'low', 'close', 'index']]
|
||||
|
||||
open = q['open']
|
||||
high = q['high']
|
||||
low = q['low']
|
||||
close = q['close']
|
||||
index = float64(q['index'])
|
||||
|
||||
istart = i * 6
|
||||
istop = istart + 6
|
||||
|
||||
# x,y detail the 6 points which connect all vertexes of a ohlc bar
|
||||
x[istart:istop] = (
|
||||
index - bar_gap,
|
||||
index,
|
||||
index,
|
||||
index,
|
||||
index,
|
||||
index + bar_gap,
|
||||
)
|
||||
y[istart:istop] = (
|
||||
open,
|
||||
open,
|
||||
low,
|
||||
high,
|
||||
close,
|
||||
close,
|
||||
)
|
||||
|
||||
# specifies that the first edge is never connected to the
|
||||
# prior bars last edge thus providing a small "gap"/"space"
|
||||
# between bars determined by ``bar_gap``.
|
||||
c[istart:istop] = (1, 1, 1, 1, 1, 0)
|
||||
|
||||
return x, y, c
|
||||
|
||||
|
||||
def gen_qpath(
|
||||
data: np.ndarray,
|
||||
start: int = 0, # XXX: do we need this?
|
||||
# 0.5 is no overlap between arms, 1.0 is full overlap
|
||||
w: float = 0.43,
|
||||
path: Optional[QtGui.QPainterPath] = None,
|
||||
|
||||
) -> QtGui.QPainterPath:
|
||||
|
||||
path_was_none = path is None
|
||||
|
||||
profiler = pg.debug.Profiler(
|
||||
msg='gen_qpath ohlc',
|
||||
disabled=not pg_profile_enabled(),
|
||||
ms_threshold=ms_slower_then,
|
||||
)
|
||||
|
||||
x, y, c = path_arrays_from_ohlc(
|
||||
data,
|
||||
start,
|
||||
bar_gap=w,
|
||||
)
|
||||
profiler("generate stream with numba")
|
||||
|
||||
# TODO: numba the internals of this!
|
||||
path = pg.functions.arrayToQPath(
|
||||
x,
|
||||
y,
|
||||
connect=c,
|
||||
path=path,
|
||||
)
|
||||
|
||||
# avoid mem allocs if possible
|
||||
if path_was_none:
|
||||
path.reserve(path.capacity())
|
||||
|
||||
profiler("generate path with arrayToQPath")
|
||||
|
||||
return path
|
||||
|
||||
|
||||
class BarItems(pg.GraphicsObject):
|
||||
'''
|
||||
"Price range" bars graphics rendered from a OHLC sampled sequence.
|
||||
|
|
@ -159,7 +274,7 @@ class BarItems(pg.GraphicsObject):
|
|||
|
||||
'''
|
||||
hist, last = ohlc[:-1], ohlc[-1]
|
||||
self.path = gen_ohlc_qpath(hist, start, self.w)
|
||||
self.path = gen_qpath(hist, start, self.w)
|
||||
|
||||
# save graphics for later reference and keep track
|
||||
# of current internal "last index"
|
||||
|
|
|
|||
|
|
@ -1,256 +0,0 @@
|
|||
# piker: trading gear for hackers
|
||||
# Copyright (C) 2018-present Tyler Goodlet (in stewardship of piker0)
|
||||
|
||||
# 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/>.
|
||||
"""
|
||||
Super fast ``QPainterPath`` generation related operator routines.
|
||||
|
||||
"""
|
||||
from typing import (
|
||||
Optional,
|
||||
)
|
||||
|
||||
import numpy as np
|
||||
from numpy.lib import recfunctions as rfn
|
||||
from numba import njit, float64, int64 # , optional
|
||||
import pyqtgraph as pg
|
||||
from PyQt5 import QtGui
|
||||
# from PyQt5.QtCore import QLineF, QPointF
|
||||
|
||||
from ..data._sharedmem import (
|
||||
ShmArray,
|
||||
)
|
||||
from .._profile import pg_profile_enabled, ms_slower_then
|
||||
from ._compression import (
|
||||
# ohlc_flatten,
|
||||
ds_m4,
|
||||
)
|
||||
|
||||
|
||||
def xy_downsample(
|
||||
x,
|
||||
y,
|
||||
px_width,
|
||||
uppx,
|
||||
|
||||
x_spacer: float = 0.5,
|
||||
|
||||
) -> tuple[np.ndarray, np.ndarray]:
|
||||
|
||||
# downsample whenever more then 1 pixels per datum can be shown.
|
||||
# always refresh data bounds until we get diffing
|
||||
# working properly, see above..
|
||||
bins, x, y = ds_m4(
|
||||
x,
|
||||
y,
|
||||
px_width=px_width,
|
||||
uppx=uppx,
|
||||
# log_scale=bool(uppx)
|
||||
)
|
||||
|
||||
# flatten output to 1d arrays suitable for path-graphics generation.
|
||||
x = np.broadcast_to(x[:, None], y.shape)
|
||||
x = (x + np.array(
|
||||
[-x_spacer, 0, 0, x_spacer]
|
||||
)).flatten()
|
||||
y = y.flatten()
|
||||
|
||||
return x, y
|
||||
|
||||
|
||||
@njit(
|
||||
# TODO: for now need to construct this manually for readonly arrays, see
|
||||
# https://github.com/numba/numba/issues/4511
|
||||
# ntypes.tuple((float64[:], float64[:], float64[:]))(
|
||||
# numba_ohlc_dtype[::1], # contiguous
|
||||
# int64,
|
||||
# optional(float64),
|
||||
# ),
|
||||
nogil=True
|
||||
)
|
||||
def path_arrays_from_ohlc(
|
||||
data: np.ndarray,
|
||||
start: int64,
|
||||
bar_gap: float64 = 0.43,
|
||||
|
||||
) -> np.ndarray:
|
||||
'''
|
||||
Generate an array of lines objects from input ohlc data.
|
||||
|
||||
'''
|
||||
size = int(data.shape[0] * 6)
|
||||
|
||||
x = np.zeros(
|
||||
# data,
|
||||
shape=size,
|
||||
dtype=float64,
|
||||
)
|
||||
y, c = x.copy(), x.copy()
|
||||
|
||||
# TODO: report bug for assert @
|
||||
# /home/goodboy/repos/piker/env/lib/python3.8/site-packages/numba/core/typing/builtins.py:991
|
||||
for i, q in enumerate(data[start:], start):
|
||||
|
||||
# TODO: ask numba why this doesn't work..
|
||||
# open, high, low, close, index = q[
|
||||
# ['open', 'high', 'low', 'close', 'index']]
|
||||
|
||||
open = q['open']
|
||||
high = q['high']
|
||||
low = q['low']
|
||||
close = q['close']
|
||||
index = float64(q['index'])
|
||||
|
||||
istart = i * 6
|
||||
istop = istart + 6
|
||||
|
||||
# x,y detail the 6 points which connect all vertexes of a ohlc bar
|
||||
x[istart:istop] = (
|
||||
index - bar_gap,
|
||||
index,
|
||||
index,
|
||||
index,
|
||||
index,
|
||||
index + bar_gap,
|
||||
)
|
||||
y[istart:istop] = (
|
||||
open,
|
||||
open,
|
||||
low,
|
||||
high,
|
||||
close,
|
||||
close,
|
||||
)
|
||||
|
||||
# specifies that the first edge is never connected to the
|
||||
# prior bars last edge thus providing a small "gap"/"space"
|
||||
# between bars determined by ``bar_gap``.
|
||||
c[istart:istop] = (1, 1, 1, 1, 1, 0)
|
||||
|
||||
return x, y, c
|
||||
|
||||
|
||||
def gen_ohlc_qpath(
|
||||
data: np.ndarray,
|
||||
start: int = 0, # XXX: do we need this?
|
||||
# 0.5 is no overlap between arms, 1.0 is full overlap
|
||||
w: float = 0.43,
|
||||
path: Optional[QtGui.QPainterPath] = None,
|
||||
|
||||
) -> QtGui.QPainterPath:
|
||||
|
||||
path_was_none = path is None
|
||||
|
||||
profiler = pg.debug.Profiler(
|
||||
msg='gen_qpath ohlc',
|
||||
disabled=not pg_profile_enabled(),
|
||||
ms_threshold=ms_slower_then,
|
||||
)
|
||||
|
||||
x, y, c = path_arrays_from_ohlc(
|
||||
data,
|
||||
start,
|
||||
bar_gap=w,
|
||||
)
|
||||
profiler("generate stream with numba")
|
||||
|
||||
# TODO: numba the internals of this!
|
||||
path = pg.functions.arrayToQPath(
|
||||
x,
|
||||
y,
|
||||
connect=c,
|
||||
path=path,
|
||||
)
|
||||
|
||||
# avoid mem allocs if possible
|
||||
if path_was_none:
|
||||
path.reserve(path.capacity())
|
||||
|
||||
profiler("generate path with arrayToQPath")
|
||||
|
||||
return path
|
||||
|
||||
|
||||
def ohlc_to_line(
|
||||
ohlc_shm: ShmArray,
|
||||
fields: list[str] = ['open', 'high', 'low', 'close']
|
||||
|
||||
) -> tuple[
|
||||
int, # flattened first index
|
||||
int, # flattened last index
|
||||
np.ndarray,
|
||||
np.ndarray,
|
||||
]:
|
||||
'''
|
||||
Convert an input struct-array holding OHLC samples into a pair of
|
||||
flattened x, y arrays with the same size (datums wise) as the source
|
||||
data.
|
||||
|
||||
'''
|
||||
y_out = ohlc_shm.ustruct(fields)
|
||||
first = ohlc_shm._first.value
|
||||
last = ohlc_shm._last.value
|
||||
|
||||
# write pushed data to flattened copy
|
||||
y_out[first:last] = rfn.structured_to_unstructured(
|
||||
ohlc_shm.array[fields]
|
||||
)
|
||||
|
||||
# generate an flat-interpolated x-domain
|
||||
x_out = (
|
||||
np.broadcast_to(
|
||||
ohlc_shm._array['index'][:, None],
|
||||
(
|
||||
ohlc_shm._array.size,
|
||||
# 4, # only ohlc
|
||||
y_out.shape[1],
|
||||
),
|
||||
) + np.array([-0.5, 0, 0, 0.5])
|
||||
)
|
||||
assert y_out.any()
|
||||
|
||||
return (
|
||||
first,
|
||||
last,
|
||||
x_out,
|
||||
y_out,
|
||||
)
|
||||
|
||||
|
||||
def to_step_format(
|
||||
shm: ShmArray,
|
||||
data_field: str,
|
||||
index_field: str = 'index',
|
||||
|
||||
) -> tuple[int, np.ndarray, np.ndarray]:
|
||||
'''
|
||||
Convert an input 1d shm array to a "step array" format
|
||||
for use by path graphics generation.
|
||||
|
||||
'''
|
||||
first = shm._first.value
|
||||
i = shm._array['index'].copy()
|
||||
out = shm._array[data_field].copy()
|
||||
|
||||
x_out = np.broadcast_to(
|
||||
i[:, None],
|
||||
(i.size, 2),
|
||||
) + np.array([-0.5, 0.5])
|
||||
|
||||
y_out = np.empty((len(out), 2), dtype=out.dtype)
|
||||
y_out[:] = out[:, np.newaxis]
|
||||
|
||||
# start y at origin level
|
||||
y_out[0, 0] = 0
|
||||
return first, x_out, y_out
|
||||
Loading…
Reference in New Issue